WorldWideScience

Sample records for technology forecast assessments

  1. Innovative activity of high-technology companies as assessment and forecasting object

    Directory of Open Access Journals (Sweden)

    A. E. Sklyarov

    2016-01-01

    Full Text Available Innovation activities, as well as innovations, are closely related meanings, and like many others economical definitions, have a broad range of meanings. Main characteristics and attributes of innovation involves new or significantly improved product, that’s being used, or in other words, found its application, and innovative activities – activities focused on realization of innovations. In this article, innovations are mainly considered in terms of high-technology production, evidence from Russian space industry. There are 5 basic stages of lifecycle of innovative project in considered industry: initiation, development, realization, expansion, consumption. Practically, third or fourth, or even both of these stages, often missing because there is no need of them. R&D activities, or even further serial production, based on previous developments, is an innovation activity, because these activities are stages of innovative projects lifecycle itself. Then it seems legit, to draw a conclusion, that in terms of high-technology production, company’s primary activity equals innovative activity. Basic characteristics of innovative activity of high-technology companies as assessment and forecasting object involves high level of uncertainty at every stage of projects lifecycle, high dependency on funding level of this activity, and high level and erratic structure of risk. All the above mentioned, means that assessment and forecasting of innovative activity of high-technology companies, needs development of its own methodological tools for each industry.

  2. A formulation of multidimensional growth models for the assessment and forecast of technology attributes

    Science.gov (United States)

    Danner, Travis W.

    Developing technology systems requires all manner of investment---engineering talent, prototypes, test facilities, and more. Even for simple design problems the investment can be substantial; for complex technology systems, the development costs can be staggering. The profitability of a corporation in a technology-driven industry is crucially dependent on maximizing the effectiveness of research and development investment. Decision-makers charged with allocation of this investment are forced to choose between the further evolution of existing technologies and the pursuit of revolutionary technologies. At risk on the one hand is excessive investment in an evolutionary technology which has only limited availability for further improvement. On the other hand, the pursuit of a revolutionary technology may mean abandoning momentum and the potential for substantial evolutionary improvement resulting from the years of accumulated knowledge. The informed answer to this question, evolutionary or revolutionary, requires knowledge of the expected rate of improvement and the potential a technology offers for further improvement. This research is dedicated to formulating the assessment and forecasting tools necessary to acquire this knowledge. The same physical laws and principles that enable the development and improvement of specific technologies also limit the ultimate capability of those technologies. Researchers have long used this concept as the foundation for modeling technological advancement through extrapolation by analogy to biological growth models. These models are employed to depict technology development as it asymptotically approaches limits established by the fundamental principles on which the technological approach is based. This has proven an effective and accurate approach to modeling and forecasting simple single-attribute technologies. With increased system complexity and the introduction of multiple system objectives, however, the usefulness of this

  3. A Delphi forecast of technology in education

    Science.gov (United States)

    Robinson, B. E.

    1973-01-01

    The results are reported of a Delphi forecast of the utilization and social impacts of large-scale educational telecommunications technology. The focus is on both forecasting methodology and educational technology. The various methods of forecasting used by futurists are analyzed from the perspective of the most appropriate method for a prognosticator of educational technology, and review and critical analysis are presented of previous forecasts and studies. Graphic responses, summarized comments, and a scenario of education in 1990 are presented.

  4. Forecasting and management of technology

    National Research Council Canada - National Science Library

    Roper, A. T

    2011-01-01

    .... The scope of this edition has broadened to include management of technology content that is relevant to now to executives in organizations while updating and strengthening the technology forecasting...

  5. Technology and demand forecasting for carbon capture and storage technology in South Korea

    International Nuclear Information System (INIS)

    Shin, Jungwoo; Lee, Chul-Yong; Kim, Hongbum

    2016-01-01

    Among the various alternatives available to reduce greenhouse gas (GHG) emissions, carbon capture and storage (CCS) is considered to be a prospective technology that could both improve economic growth and meet GHG emission reduction targets. Despite the importance of CCS, however, studies of technology and demand forecasting for CCS are scarce. This study bridges this gap in the body of knowledge on this topic by forecasting CCS technology and demand based on an integrated model. For technology forecasting, a logistic model and patent network analysis are used to compare the competitiveness of CCS technology for selected countries. For demand forecasting, a competition diffusion model is adopted to consider competition among renewable energies and forecast demand. The results show that the number of patent applications for CCS technology will increase to 16,156 worldwide and to 4,790 in Korea by 2025. We also find that the United States has the most competitive CCS technology followed by Korea and France. Moreover, about 5 million tCO_2e of GHG will be reduced by 2040 if CCS technology is adopted in Korea after 2020. - Highlights: • Carbon capture and storage (CCS) can help mitigate climate change globally. • It can both improve economic growth and meet GHG emission reduction targets. • We forecast CCS technology and demand based on an integrated model. • The US has the most competitive CCS technology followed by Korea and France. • 5 million tCO_2e of GHG will be reduced by 2040 if CCS is adopted in Korea.

  6. Hydrocarbon Rocket Technology Impact Forecasting

    Science.gov (United States)

    Stuber, Eric; Prasadh, Nishant; Edwards, Stephen; Mavris, Dimitri N.

    2012-01-01

    Forecasting method is a normative forecasting technique that allows the designer to quantify the effects of adding new technologies on a given design. This method can be used to assess and identify the necessary technological improvements needed to close the gap that exists between the current design and one that satisfies all constraints imposed on the design. The TIF methodology allows for more design knowledge to be brought to the earlier phases of the design process, making use of tools such as Quality Function Deployments, Morphological Matrices, Response Surface Methodology, and Monte Carlo Simulations.2 This increased knowledge allows for more informed decisions to be made earlier in the design process, resulting in shortened design cycle time. This paper will investigate applying the TIF method, which has been widely used in aircraft applications, to the conceptual design of a hydrocarbon rocket engine. In order to reinstate a manned presence in space, the U.S. must develop an affordable and sustainable launch capability. Hydrocarbon-fueled rockets have drawn interest from numerous major government and commercial entities because they offer a low-cost heavy-lift option that would allow for frequent launches1. However, the development of effective new hydrocarbon rockets would likely require new technologies in order to overcome certain design constraints. The use of advanced design methods, such as the TIF method, enables the designer to identify key areas in need of improvement, allowing one to dial in a proposed technology and assess its impact on the system. Through analyses such as this one, a conceptual design for a hydrocarbon-fueled vehicle that meets all imposed requirements can be achieved.

  7. Post LANDSAT D Advanced Concept Evaluation (PLACE). [with emphasis on mission planning, technological forecasting, and user requirements

    Science.gov (United States)

    1977-01-01

    An outline is given of the mission objectives and requirements, system elements, system concepts, technology requirements and forecasting, and priority analysis for LANDSAT D. User requirements and mission analysis and technological forecasting are emphasized. Mission areas considered include agriculture, range management, forestry, geology, land use, water resources, environmental quality, and disaster assessment.

  8. A Multi-scale, Multi-Model, Machine-Learning Solar Forecasting Technology

    Energy Technology Data Exchange (ETDEWEB)

    Hamann, Hendrik F. [IBM, Yorktown Heights, NY (United States). Thomas J. Watson Research Center

    2017-05-31

    The goal of the project was the development and demonstration of a significantly improved solar forecasting technology (short: Watt-sun), which leverages new big data processing technologies and machine-learnt blending between different models and forecast systems. The technology aimed demonstrating major advances in accuracy as measured by existing and new metrics which themselves were developed as part of this project. Finally, the team worked with Independent System Operators (ISOs) and utilities to integrate the forecasts into their operations.

  9. Computer technology forecasting at the National Laboratories

    International Nuclear Information System (INIS)

    Peskin, A.M.

    1980-01-01

    The DOE Office of ADP Management organized a group of scientists and computer professionals, mostly from their own national laboratories, to prepare an annually updated technology forecast to accompany the Department's five-year ADP Plan. The activities of the task force were originally reported in an informal presentation made at the ACM Conference in 1978. This presentation represents an update of that report. It also deals with the process of applying the results obtained at a particular computing center, Brookhaven National Laboratory. Computer technology forecasting is a difficult and hazardous endeavor, but it can reap considerable advantage. The forecast performed on an industry-wide basis can be applied to the particular needs of a given installation, and thus give installation managers considerable guidance in planning. A beneficial side effect of this process is that it forces installation managers, who might otherwise tend to preoccupy themselves with immediate problems, to focus on longer term goals and means to their ends

  10. Assessing the accuracy of forecasting: applying standard diagnostic assessment tools to a health technology early warning system.

    Science.gov (United States)

    Simpson, Sue; Hyde, Chris; Cook, Alison; Packer, Claire; Stevens, Andrew

    2004-01-01

    Early warning systems are an integral part of many health technology assessment programs. Despite this finding, to date, there have been no quantitative evaluations of the accuracy of predictions made by these systems. We report a study evaluating the accuracy of predictions made by the main United Kingdom early warning system. As prediction of impact is analogous to diagnosis, a method normally applied to determine the accuracy of diagnostic tests was used. The sensitivity, specificity, and predictive values of the National Horizon Scanning Centre's prediction methods were estimated with reference to an (imperfect) gold standard, that is, expert opinion of impact 3 to 5 years after prediction. The sensitivity of predictions was 71 percent (95 percent confidence interval [CI], 0.36-0.92), and the specificity was 73 percent (95 percent CI, 0.64-0.8). The negative predictive value was 98 percent (95 percent CI, 0.92-0.99), and the positive predictive value was 14 percent (95 percent CI, 0.06-0.3). Forecasting is difficult, but the results suggest that this early warning system's predictions have an acceptable level of accuracy. However, there are caveats. The first is that early warning systems may themselves reduce the impact of a technology, as helping to control adoption and diffusion is their main purpose. The second is that the use of an imperfect gold standard may bias the results. As early warning systems are viewed as an increasingly important component of health technology assessment and decision making, their outcomes must be evaluated. The method used here should be investigated further and the accuracy of other early warning systems explored.

  11. Past speculations of future health technologies: a description of technologies predicted in 15 forecasting studies published between 1986 and 2010.

    Science.gov (United States)

    Doos, Lucy; Packer, Claire; Ward, Derek; Simpson, Sue; Stevens, Andrew

    2017-07-31

    To describe and classify health technologies predicted in forecasting studies. A portrait describing health technologies predicted in 15 forecasting studies published between 1986 and 2010 that were identified in a previous systematic review. Health technologies are classified according to their type, purpose and clinical use; relating these to the original purpose and timing of the forecasting studies. All health-related technologies predicted in 15 forecasting studies identified in a previously published systematic review. Outcomes related to (1) each forecasting study including country, year, intention and forecasting methods used and (2) the predicted technologies including technology type, purpose, targeted clinical area and forecast timeframe. Of the 896 identified health-related technologies, 685 (76.5%) were health technologies with an explicit or implied health application and included in our study. Of these, 19.1% were diagnostic or imaging tests, 14.3% devices or biomaterials, 12.6% information technology systems, eHealth or mHealth and 12% drugs. The majority of the technologies were intended to treat or manage disease (38.1%) or diagnose or monitor disease (26.1%). The most frequent targeted clinical areas were infectious diseases followed by cancer, circulatory and nervous system disorders. The most frequent technology types were for: infectious diseases-prophylactic vaccines (45.8%), cancer-drugs (40%), circulatory disease-devices and biomaterials (26.3%), and diseases of the nervous system-equally devices and biomaterials (25%) and regenerative medicine (25%). The mean timeframe for forecasting was 11.6 years (range 0-33 years, median=10, SD=6.6). The forecasting timeframe significantly differed by technology type (p=0.002), the intent of the forecasting group (p<0.001) and the methods used (p<001). While description and classification of predicted health-related technologies is crucial in preparing healthcare systems for adopting new innovations

  12. Forecasting the Success of Implementing Sensors Advanced Manufacturing Technology

    Directory of Open Access Journals (Sweden)

    Cheng-Shih Su

    2014-08-01

    Full Text Available This paper is presented fuzzy preference relations approach to forecast the success of implementing sensors advanced manufacturing technology (AMT. In the manufacturing environment, performance measurement is based on different quantitative and qualitative factors. This study proposes an analytic hierarchical prediction model based on fuzzy preference relations to help the organizations become aware of the essential factors affecting the AMT implementation, forecasting the chance of successful implementing sensors AMT, as well as identifying the actions necessary before implementing sensors AMT. Then predicted success/failure values are obtained to enable organizations to decide whether to initiate sensors AMT, inhibit adoption or take remedial actions to increase the possibility of successful sensors AMT initiatives. This proposed approach is demonstrated with a real case study involving six influential factors assessed by nine evaluators solicited from a semiconductor engineering incorporation located in Taiwan.

  13. Past speculations of the future: a review of the methods used for forecasting emerging health technologies.

    Science.gov (United States)

    Doos, Lucy; Packer, Claire; Ward, Derek; Simpson, Sue; Stevens, Andrew

    2016-03-10

    Forecasting can support rational decision-making around the introduction and use of emerging health technologies and prevent investment in technologies that have limited long-term potential. However, forecasting methods need to be credible. We performed a systematic search to identify the methods used in forecasting studies to predict future health technologies within a 3-20-year timeframe. Identification and retrospective assessment of such methods potentially offer a route to more reliable prediction. Systematic search of the literature to identify studies reported on methods of forecasting in healthcare. People are not needed in this study. The authors searched MEDLINE, EMBASE, PsychINFO and grey literature sources, and included articles published in English that reported their methods and a list of identified technologies. Studies reporting methods used to predict future health technologies within a 3-20-year timeframe with an identified list of individual healthcare technologies. Commercially sponsored reviews, long-term futurology studies (with over 20-year timeframes) and speculative editorials were excluded. 15 studies met our inclusion criteria. Our results showed that the majority of studies (13/15) consulted experts either alone or in combination with other methods such as literature searching. Only 2 studies used more complex forecasting tools such as scenario building. The methodological fundamentals of formal 3-20-year prediction are consistent but vary in details. Further research needs to be conducted to ascertain if the predictions made were accurate and whether accuracy varies by the methods used or by the types of technologies identified. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

  14. Information Technology Resources Assessment

    Energy Technology Data Exchange (ETDEWEB)

    1993-04-01

    The Information Technology Resources Assessment (ITRA) is being published as a companion document to the Department of Energy (DOE) FY 1994--FY 1998 Information Resources Management Long-Range Plan. This document represents a collaborative effort between the Office of Information Resources Management and the Office of Energy Research that was undertaken to achieve, in part, the Technology Strategic Objective of IRM Vision 21. An integral part of this objective, technology forecasting provides an understanding of the information technology horizon and presents a perspective and focus on technologies of particular interest to DOE program activities. Specifically, this document provides site planners with an overview of the status and use of new information technology for their planning consideration.

  15. Operational flash flood forecasting platform based on grid technology

    Science.gov (United States)

    Thierion, V.; Ayral, P.-A.; Angelini, V.; Sauvagnargues-Lesage, S.; Nativi, S.; Payrastre, O.

    2009-04-01

    Flash flood events of south of France such as the 8th and 9th September 2002 in the Grand Delta territory caused important economic and human damages. Further to this catastrophic hydrological situation, a reform of flood warning services have been initiated (set in 2006). Thus, this political reform has transformed the 52 existing flood warning services (SAC) in 22 flood forecasting services (SPC), in assigning them territories more hydrological consistent and new effective hydrological forecasting mission. Furthermore, national central service (SCHAPI) has been created to ease this transformation and support local services in their new objectives. New functioning requirements have been identified: - SPC and SCHAPI carry the responsibility to clearly disseminate to public organisms, civil protection actors and population, crucial hydrologic information to better anticipate potential dramatic flood event, - a new effective hydrological forecasting mission to these flood forecasting services seems essential particularly for the flash floods phenomenon. Thus, models improvement and optimization was one of the most critical requirements. Initially dedicated to support forecaster in their monitoring mission, thanks to measuring stations and rainfall radar images analysis, hydrological models have to become more efficient in their capacity to anticipate hydrological situation. Understanding natural phenomenon occuring during flash floods mainly leads present hydrological research. Rather than trying to explain such complex processes, the presented research try to manage the well-known need of computational power and data storage capacities of these services. Since few years, Grid technology appears as a technological revolution in high performance computing (HPC) allowing large-scale resource sharing, computational power using and supporting collaboration across networks. Nowadays, EGEE (Enabling Grids for E-science in Europe) project represents the most important

  16. Application research for 4D technology in flood forecasting and evaluation

    Science.gov (United States)

    Li, Ziwei; Liu, Yutong; Cao, Hongjie

    1998-08-01

    In order to monitor the region which disaster flood happened frequently in China, satisfy the great need of province governments for high accuracy monitoring and evaluated data for disaster and improve the efficiency for repelling disaster, under the Ninth Five-year National Key Technologies Programme, the method was researched for flood forecasting and evaluation using satellite and aerial remoted sensed image and land monitor data. The effective and practicable flood forecasting and evaluation system was established and DongTing Lake was selected as the test site. Modern Digital photogrammetry, remote sensing and GIS technology was used in this system, the disastrous flood could be forecasted and loss can be evaluated base on '4D' (DEM -- Digital Elevation Model, DOQ -- Digital OrthophotoQuads, DRG -- Digital Raster Graph, DTI -- Digital Thematic Information) disaster background database. The technology of gathering and establishing method for '4D' disaster environment background database, application technology for flood forecasting and evaluation based on '4D' background data and experimental results for DongTing Lake test site were introduced in detail in this paper.

  17. Analyses and Forecasting of Smart Grid Technological Dynamics

    Directory of Open Access Journals (Sweden)

    I. V. Danilin

    2017-01-01

    Full Text Available Purpose: this paper analyzes and forecasts medium- to long-term dynamics of Smart Grid technology developments considering both patent activity and socio-economic (demand-side issues and requirements of economy and power system factors. Methods: for the analysis of Smart Grid patent data (IIP, USPTO, and WIPO patent databases used we apply syntactic semantic analysis of texts in natural languages and logistic curve-based method. We propose Exactus Patent system for intelligent full-text search and analysis of patents (results verified with Thomson Innovation and TotalPatent patent search systems. For interpretation of revealed dynamics and forecasting of future conditions we identify key long-term socio-economic factors drivers for Smart Grid development. Elements of C. Christensen (disruptive innovations and G. Dosi (technological trajectories theories were applied. Results: the study reveals a fast technological transformation within the Smart Grid domain due to the long-term socio-economic factors such as rise of renewables; energy efficiency and energy security issues; environmental constraints and shift of values; requirements for accelerated grid construction (in developing economies and grid modernization (in developed ones; ongoing economy-wide digitalization. Due to the limited economic effects of Smart Grid roll-outs (considering major requirements of economic agents and society and considering progressions of patent dynamics, authors forecasts technology stagnation (in terms of number of patents growth by the end of 2010-s as end of Gartner`s hype development stage. Conclusions and Relevance: a foreseen change in dynamics of Smart Grid technology development is interpreted as a manifestation of sinusoidal fluctuations in technology development for disruptive technologies (supported with OECD data. A longer cycle (in comparison with other disruptive technologies is interpreted as consequence of technology and industry specifics

  18. Forecasting the Success of Implementing Sensors Advanced Manufacturing Technology

    OpenAIRE

    Cheng-Shih Su; Shu-Chen Hsu

    2014-01-01

    This paper is presented fuzzy preference relations approach to forecast the success of implementing sensors advanced manufacturing technology (AMT). In the manufacturing environment, performance measurement is based on different quantitative and qualitative factors. This study proposes an analytic hierarchical prediction model based on fuzzy preference relations to help the organizations become aware of the essential factors affecting the AMT implementation, forecasting the chance of successf...

  19. Uncertainty Assessment: Reservoir Inflow Forecasting with Ensemble Precipitation Forecasts and HEC-HMS

    Directory of Open Access Journals (Sweden)

    Sheng-Chi Yang

    2014-01-01

    Full Text Available During an extreme event, having accurate inflow forecasting with enough lead time helps reservoir operators decrease the impact of floods downstream. Furthermore, being able to efficiently operate reservoirs could help maximize flood protection while saving water for drier times of the year. This study combines ensemble quantitative precipitation forecasts and a hydrological model to provide a 3-day reservoir inflow in the Shihmen Reservoir, Taiwan. A total of six historical typhoons were used for model calibration, validation, and application. An understanding of cascaded uncertainties from the numerical weather model through the hydrological model is necessary for a better use for forecasting. This study thus conducted an assessment of forecast uncertainty on magnitude and timing of peak and cumulative inflows. It found that using the ensemble-mean had less uncertainty than randomly selecting individual member. The inflow forecasts with shorter length of cumulative time had a higher uncertainty. The results showed that using the ensemble precipitation forecasts with the hydrological model would have the advantage of extra lead time and serve as a valuable reference for operating reservoirs.

  20. Space power needs and forecasted technologies for the 1990s and beyond

    International Nuclear Information System (INIS)

    Buden, D.; Albert, T.

    1987-01-01

    A new generation of reactors for electric power will be available for space missions to satisfy military and civilian needs in the 1990s and beyond. To ensure a useful product, nuclear power plant development must be cognizant of other space power technologies. Major advances in solar and chemical technologies need to be considered in establishing the goals of future nuclear power plants. In addition, the mission needs are evolving into new regimes. Civilian and military power needs are forecasted to exceed anything used in space to date. Technology trend forecasts have been mapped as a function of time for solar, nuclear, chemical, and storage systems to illustrate areas where each technology provides minimum mass. Other system characteristics may dominate the usefulness of a technology on a given mission. This paper will discuss some of these factors, as well as forecast future military and civilian power needs and the status of technologies for the 1990s and 2000s. 6 references

  1. Forecasting Technological Discontinuities in the ICT Industry

    DEFF Research Database (Denmark)

    Hoisl, Karin; Stelzer, Tobias; Biala, Stefanie

    2015-01-01

    in the ICT industry. The conjoint approach allows for a simulation of the forecasting process and considers utility trade-offs. The results show that for both types of experts the perceived benefit of users most highly contributes to predicting technological discontinuities. Internal experts assign more...

  2. Forecasting and observability: critical technologies for system operations with high PV penetration

    DEFF Research Database (Denmark)

    Alet, Pierre-Jean; Efthymiou, Venizelos; Graditi, Giorgio

    2016-01-01

    – Photovoltaics (ETIP PV) reviews the different use cases for these technologies, their current status, and the need for future developments. Power system operations require a real-time view of PV production for managing power reserves and for feeding shortterm forecasts. They also require forecasts on all......Forecasting and monitoring technologies for photovoltaics are required on different spatial and temporal scales by multiple actors, from the owners of PV systems to transmission system operators. In this paper the Grid integration working group of the European Technology and Innovation Platform...... timescales from the short (for dispatching purposes), where statistical models work best, to the very long (for infrastructure planning), where physics-based models are more accurate. Power system regulations are driving the development of these techniques. This application also provides a good basis...

  3. Transport project evaluation: feasibility risk assessment and scenario forecasting

    DEFF Research Database (Denmark)

    Salling, Kim Bang; Leleur, Steen

    2017-01-01

    This paper presents a new approach to transport project assessment in terms of feasibility risk assessment and reference class forecasting. Conventionally, transport project assessment is based upon a Cost-Benefit Analysis (CBA) where evaluation criteria such as Benefit Cost Ratios (BCR...... on the preliminary construction cost estimates. Hereafter, a quantitative risk analysis is provided making use of Monte Carlo simulation. This approach facilitates random input parameters based upon reference class forecasting, hence, a parameter data fit has been performed in order to obtain validated probability...... Scenario Forecasting (RSF) frame. The RSF is anchored in the cost-benefit analysis; thus, it provides decision-makers with a quantitative mean of assessing the transport infrastructure project. First, the RSF method introduces uncertainties within the CBA by applying Optimism Bias uplifts...

  4. How accurate are forecasts of costs of energy? A methodological contribution

    International Nuclear Information System (INIS)

    Siddons, Craig; Allan, Grant; McIntyre, Stuart

    2015-01-01

    Forecasts of the cost of energy are typically presented as point estimates; however forecasts are seldom accurate, which makes it important to understand the uncertainty around these point estimates. The scale of the differences between forecasts and outturns (i.e. contemporary estimates) of costs may have important implications for government decisions on the appropriate form (and level) of support, modelling energy scenarios or industry investment appraisal. This paper proposes a methodology to assess the accuracy of cost forecasts. We apply this to levelised costs of energy for different generation technologies due to the availability of comparable forecasts and contemporary estimates, however the same methodology could be applied to the components of levelised costs, such as capital costs. The estimated “forecast errors” capture the accuracy of previous forecasts and can provide objective bounds to the range around current forecasts for such costs. The results from applying this method are illustrated using publicly available data for on- and off-shore wind, Nuclear and CCGT technologies, revealing the possible scale of “forecast errors” for these technologies. - Highlights: • A methodology to assess the accuracy of forecasts of costs of energy is outlined. • Method applied to illustrative data for four electricity generation technologies. • Results give an objective basis for sensitivity analysis around point estimates.

  5. An Interval Estimation Method of Patent Keyword Data for Sustainable Technology Forecasting

    Directory of Open Access Journals (Sweden)

    Daiho Uhm

    2017-11-01

    Full Text Available Technology forecasting (TF is forecasting the future state of a technology. It is exciting to know the future of technologies, because technology changes the way we live and enhances the quality of our lives. In particular, TF is an important area in the management of technology (MOT for R&D strategy and new product development. Consequently, there are many studies on TF. Patent analysis is one method of TF because patents contain substantial information regarding developed technology. The conventional methods of patent analysis are based on quantitative approaches such as statistics and machine learning. The most traditional TF methods based on patent analysis have a common problem. It is the sparsity of patent keyword data structured from collected patent documents. After preprocessing with text mining techniques, most frequencies of technological keywords in patent data have values of zero. This problem creates a disadvantage for the performance of TF, and we have trouble analyzing patent keyword data. To solve this problem, we propose an interval estimation method (IEM. Using an adjusted Wald confidence interval called the Agresti–Coull confidence interval, we construct our IEM for efficient TF. In addition, we apply the proposed method to forecast the technology of an innovative company. To show how our work can be applied in the real domain, we conduct a case study using Apple technology.

  6. Recent advances in flood forecasting and flood risk assessment

    Directory of Open Access Journals (Sweden)

    G. Arduino

    2005-01-01

    Full Text Available Recent large floods in Europe have led to increased interest in research and development of flood forecasting systems. Some of these events have been provoked by some of the wettest rainfall periods on record which has led to speculation that such extremes are attributable in some measure to anthropogenic global warming and represent the beginning of a period of higher flood frequency. Whilst current trends in extreme event statistics will be difficult to discern, conclusively, there has been a substantial increase in the frequency of high floods in the 20th century for basins greater than 2x105 km2. There is also increasing that anthropogenic forcing of climate change may lead to an increased probability of extreme precipitation and, hence, of flooding. There is, therefore, major emphasis on the improvement of operational flood forecasting systems in Europe, with significant European Community spending on research and development on prototype forecasting systems and flood risk management projects. This Special Issue synthesises the most relevant scientific and technological results presented at the International Conference on Flood Forecasting in Europe held in Rotterdam from 3-5 March 2003. During that meeting 150 scientists, forecasters and stakeholders from four continents assembled to present their work and current operational best practice and to discuss future directions of scientific and technological efforts in flood prediction and prevention. The papers presented at the conference fall into seven themes, as follows.

  7. PATTERNS OF SCIENTIFIC AND TECHNOLOGICAL DEVELOPMENT AND THEIR USE IN FORECASTING

    Directory of Open Access Journals (Sweden)

    N. I. Komkov

    2010-01-01

    Full Text Available In article laws of scientifically-technological development are considered. Their number concern traditional, base and new, formed. Possibilities and ways of the account of the listed laws are shown at forecasting of prospects of scientifically-technological development.

  8. International survey for good practices in forecasting uncertainty assessment and communication

    Science.gov (United States)

    Berthet, Lionel; Piotte, Olivier

    2014-05-01

    Achieving technically sound flood forecasts is a crucial objective for forecasters but remains of poor use if the users do not understand properly their significance and do not use it properly in decision making. One usual way to precise the forecasts limitations is to communicate some information about their uncertainty. Uncertainty assessment and communication to stakeholders are thus important issues for operational flood forecasting services (FFS) but remain open fields for research. French FFS wants to publish graphical streamflow and level forecasts along with uncertainty assessment in near future on its website (available to the greater public). In order to choose the technical options best adapted to its operational context, it carried out a survey among more than 15 fellow institutions. Most of these are providing forecasts and warnings to civil protection officers while some were mostly working for hydroelectricity suppliers. A questionnaire has been prepared in order to standardize the analysis of the practices of the surveyed institutions. The survey was conducted by gathering information from technical reports or from the scientific literature, as well as 'interviews' driven by phone, email discussions or meetings. The questionnaire helped in the exploration of practices in uncertainty assessment, evaluation and communication. Attention was paid to the particular context within which every insitution works, in the analysis drawn from raw results. Results show that most services interviewed assess their forecasts uncertainty. However, practices can differ significantly from a country to another. Popular techniques are ensemble approaches. They allow to take into account several uncertainty sources. Statistical past forecasts analysis (such as the quantile regressions) are also commonly used. Contrary to what was expected, only few services emphasize the role of the forecaster (subjective assessment). Similar contrasts can be observed in uncertainty

  9. Forecastability as a Design Criterion in Wind Resource Assessment: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, J.; Hodge, B. M.

    2014-04-01

    This paper proposes a methodology to include the wind power forecasting ability, or 'forecastability,' of a site as a design criterion in wind resource assessment and wind power plant design stages. The Unrestricted Wind Farm Layout Optimization (UWFLO) methodology is adopted to maximize the capacity factor of a wind power plant. The 1-hour-ahead persistence wind power forecasting method is used to characterize the forecastability of a potential wind power plant, thereby partially quantifying the integration cost. A trade-off between the maximum capacity factor and the forecastability is investigated.

  10. Reference Scenario Forecasting: A New Approach to Transport Project Assessment

    DEFF Research Database (Denmark)

    Salling, Kim Bang; Leleur, Steen; Skougaard, Britt Zoëga

    2010-01-01

    This paper presents a new approach to transport project assessment in terms of feasibility risk assessment and reference class forecasting. Normally, transport project assessment is based upon a cost-benefit approach where evaluation criteria such as net present values are obtained. Recent research...... construction cost estimates. Hereafter, a quantitative risk analysis is provided making use of Monte Carlo simulation. This stochastic approach facilitates random input parameters based upon reference class forecasting, hence, a parameter data fit has been performed in order to obtain validated probability...... forecasting (RSF) frame. The RSF is anchored in the cost-benefit analysis (CBA), thus, it provides decision-makers with a quantitative mean of assessing the transport infrastructure project. First, the RSF method introduces uncertainties within the CBA by applying Optimism Bias uplifts on the preliminary...

  11. Assessing flood forecast uncertainty with fuzzy arithmetic

    Directory of Open Access Journals (Sweden)

    de Bruyn Bertrand

    2016-01-01

    Full Text Available Providing forecasts for flow rates and water levels during floods have to be associated with uncertainty estimates. The forecast sources of uncertainty are plural. For hydrological forecasts (rainfall-runoff performed using a deterministic hydrological model with basic physics, two main sources can be identified. The first obvious source is the forcing data: rainfall forecast data are supplied in real time by meteorological forecasting services to the Flood Forecasting Service within a range between a lowest and a highest predicted discharge. These two values define an uncertainty interval for the rainfall variable provided on a given watershed. The second source of uncertainty is related to the complexity of the modeled system (the catchment impacted by the hydro-meteorological phenomenon, the number of variables that may describe the problem and their spatial and time variability. The model simplifies the system by reducing the number of variables to a few parameters. Thus it contains an intrinsic uncertainty. This model uncertainty is assessed by comparing simulated and observed rates for a large number of hydro-meteorological events. We propose a method based on fuzzy arithmetic to estimate the possible range of flow rates (and levels of water making a forecast based on possible rainfalls provided by forcing and uncertainty model. The model uncertainty is here expressed as a range of possible values. Both rainfall and model uncertainties are combined with fuzzy arithmetic. This method allows to evaluate the prediction uncertainty range. The Flood Forecasting Service of Oise and Aisne rivers, in particular, monitors the upstream watershed of the Oise at Hirson. This watershed’s area is 310 km2. Its response time is about 10 hours. Several hydrological models are calibrated for flood forecasting in this watershed and use the rainfall forecast. This method presents the advantage to be easily implemented. Moreover, it permits to be carried out

  12. Forecasting and Technology Management: Statistical Theory and Methodological Issues

    DEFF Research Database (Denmark)

    Madsen, Henning

    of directions and targets for a R and D project, monitoring of a given area by a public agency, and evaluation of the future competitive situation for a company. This paper gives a brief introduction to the field of technological forecasting especially in relation to the strategic planning process...

  13. Extravehicular Activity Technology Development Status and Forecast

    Science.gov (United States)

    Chullen, Cinda; Westheimer, David T.

    2011-01-01

    The goal of NASA s current EVA technology effort is to further develop technologies that will be used to demonstrate a robust EVA system that has application for a variety of future missions including microgravity and surface EVA. Overall the objectives will be to reduce system mass, reduce consumables and maintenance, increase EVA hardware robustness and life, increase crew member efficiency and autonomy, and enable rapid vehicle egress and ingress. Over the past several years, NASA realized a tremendous increase in EVA system development as part of the Exploration Technology Development Program and the Constellation Program. The evident demand for efficient and reliable EVA technologies, particularly regenerable technologies was apparent under these former programs and will continue to be needed as future mission opportunities arise. The technological need for EVA in space has been realized over the last several decades by the Gemini, Apollo, Skylab, Space Shuttle, and the International Space Station (ISS) programs. EVAs were critical to the success of these programs. Now with the ISS extension to 2028 in conjunction with a current forecasted need of at least eight EVAs per year, the EVA hardware life and limited availability of the Extravehicular Mobility Units (EMUs) will eventually become a critical issue. The current EMU has successfully served EVA demands by performing critical operations to assemble the ISS and provide repairs of satellites such as the Hubble Space Telescope. However, as the life of ISS and the vision for future mission opportunities are realized, a new EVA systems capability will be needed and the current architectures and technologies under development offer significant improvements over the current flight systems. In addition to ISS, potential mission applications include EVAs for missions to Near Earth Objects (NEO), Phobos, or future surface missions. Surface missions could include either exploration of the Moon or Mars. Providing an

  14. An Approach to Assess Observation Impact Based on Observation-Minus-Forecast Residuals

    Science.gov (United States)

    Todling, Ricardo

    2009-01-01

    Langland and Baker (2004) introduced an approach to assess the impact of observations on the forecasts. In that, a state-space aspect of the forecast is defined and a procedure is derived that relates changes in the aspect with changes in the initial conditions associated with the assimilation of observations) ultimately providing information about the impact of individual observations on the forecast. Some features of the approach are to be noted. The typical choice of forecast aspect employed in related works is rather arbitrary and leads to an incomplete assessment of the observing system. Furthermore, the state-space forecast aspect requires availability of a verification state that should ideally be uncorrelated with the forecast but in practice is not. Lastly, the approach involves the adjoint operator of the entire data assimilation system and as such it is constrained by the validity of this operator. In this presentation, an observation-space metric is used that, for a relatively time-homogeneous observing system, allows inferring observation impact on the forecast without some of the limitations above. Specifically, using observation-minus-forecast residuals leads to an approach with the following features: (i) it suggests a rather natural choice of forecast aspect, directly linked to the analysis system and providing full assessment of the observations; (ii) it naturally avoids introducing undesirable correlations in the forecast aspect by verifying against the observations; and (iii) it does not involve linearization and use of adjoints; therefore being applicable to any length of forecast. The state and observation-space approaches might be complementary to some degree, and involve different limitations and complexities. Illustrations are given using the NASA GEOS-5 data.

  15. Economic assessment of flood forecasts for a risk-averse decision-maker

    Science.gov (United States)

    Matte, Simon; Boucher, Marie-Amélie; Boucher, Vincent; Fortier-Filion, Thomas-Charles

    2017-04-01

    A large effort has been made over the past 10 years to promote the operational use of probabilistic or ensemble streamflow forecasts. It has also been suggested in past studies that ensemble forecasts might possess a greater economic value than deterministic forecasts. However, the vast majority of recent hydro-economic literature is based on the cost-loss ratio framework, which might be appealing for its simplicity and intuitiveness. One important drawback of the cost-loss ratio is that it implicitly assumes a risk-neutral decision maker. By definition, a risk-neutral individual is indifferent to forecasts' sharpness: as long as forecasts agree with observations on average, the risk-neutral individual is satisfied. A risk-averse individual, however, is sensitive to the level of precision (sharpness) of forecasts. This person is willing to pay to increase his or her certainty about future events. In fact, this is how insurance companies operate: the probability of seeing one's house burn down is relatively low, so the expected cost related to such event is also low. However, people are willing to buy insurance to avoid the risk, however small, of loosing everything. Similarly, in a context where people's safety and property is at stake, the typical decision maker is more risk-averse than risk-neutral. Consequently, the cost-loss ratio is not the most appropriate tool to assess the economic value of flood forecasts. This presentation describes a more realistic framework for assessing the economic value of such forecasts for flood mitigation purposes. Borrowing from economics, the Constant Absolute Risk Aversion utility function (CARA) is the central tool of this new framework. Utility functions allow explicitly accounting for the level of risk aversion of the decision maker and fully exploiting the information related to ensemble forecasts' uncertainty. Three concurrent ensemble streamflow forecasting systems are compared in terms of quality (comparison with

  16. New Technology Trends in Education: Seven Years of Forecasts and Convergence

    Science.gov (United States)

    Martin, Sergio; Diaz, Gabriel; Sancristobal, Elio; Gil, Rosario; Castro, Manuel; Peire, Juan

    2011-01-01

    Each year since 2004, a new Horizon Report has been released. Each edition attempts to forecast the most promising technologies likely to impact on education along three horizons: the short term (the year of the report), the mid-term (the next 2 years) and the long term (the next 4 years). This paper analyzes the evolution of technology trends…

  17. Technology data characterizing refrigeration in commercial buildings: Application to end-use forecasting with COMMEND 4.0

    Energy Technology Data Exchange (ETDEWEB)

    Sezgen, O.; Koomey, J.G.

    1995-12-01

    In the United States, energy consumption is increasing most rapidly in the commercial sector. Consequently, the commercial sector is becoming an increasingly important target for state and federal energy policies and also for utility-sponsored demand side management (DSM) programs. The rapid growth in commercial-sector energy consumption also makes it important for analysts working on energy policy and DSM issues to have access to energy end-use forecasting models that include more detailed representations of energy-using technologies in the commercial sector. These new forecasting models disaggregate energy consumption not only by fuel type, end use, and building type, but also by specific technology. The disaggregation of the refrigeration end use in terms of specific technologies, however, is complicated by several factors. First, the number of configurations of refrigeration cases and systems is quite large. Also, energy use is a complex function of the refrigeration-case properties and the refrigeration-system properties. The Electric Power Research Institute`s (EPRI`s) Commercial End-Use Planning System (COMMEND 4.0) and the associated data development presented in this report attempt to address the above complications and create a consistent forecasting framework. Expanding end-use forecasting models so that they address individual technology options requires characterization of the present floorstock in terms of service requirements, energy technologies used, and cost-efficiency attributes of the energy technologies that consumers may choose for new buildings and retrofits. This report describes the process by which we collected refrigeration technology data. The data were generated for COMMEND 4.0 but are also generally applicable to other end-use forecasting frameworks for the commercial sector.

  18. Hanford's self-assessment of the solid waste forecast process

    International Nuclear Information System (INIS)

    Hauth, J.; Skumanich, M.; Morgan, J.

    1996-01-01

    In fiscal year (FY) 1995 the forecast process used at Hanford to project future solid waste volumes was evaluated. Data on current and future solid waste generation are used by Hanford site planners to determine near-term and long-term planning needs. Generators who plan to ship their waste to Hanford's Solid Waste Program for treatment, storage, and disposal provide volume information on the types of waste that could be potentially generated, waste characteristics, and container types. Generators also provide limited radionuclide data and supporting assumptions. A self-assessment of the forecast process identified many effective working elements, including a well-established and systematic process for data collection, analysis and reporting; sufficient resources to obtain the necessary information; and dedicated support and analytic staff. Several areas for improvement were identified, including the need to improve confidence in the forecast data, integrate forecast data with other site-level and national data calls, enhance the electronic data collection system, and streamline the forecast process

  19. Systems dynamics modelling to assess the sustainability of renewable energy technologies in developing countries

    CSIR Research Space (South Africa)

    Brent, AC

    2011-04-01

    Full Text Available review of methods and tools applied in technology assessment. Technological Forecasting and Social Change, 75, pp. 1396-1405, 2008. [13] Sterman, J.D., Business dynamics: systems thinking and modelling for a complex world. McGraw-Hill/Irwin, New York...

  20. Technological developments in real-time operational hydrologic forecasting in the United States

    Science.gov (United States)

    Hudlow, Michael D.

    1988-09-01

    The hydrologic forecasting service of the United States spans applications and scales ranging from those associated with the issuance of flood and flash warnings to those pertaining to seasonal water supply forecasts. New technological developments (underway in or planned by the National Weather Service (NWS) in support of the Hydrologic Program) are carried out as combined efforts by NWS headquarters and field personnel in cooperation with other organizations. These developments fall into two categories: hardware and software systems technology, and hydrometeorological analysis and prediction technology. Research, development, and operational implementation in progress in both of these areas are discussed. Cornerstones of an overall NWS modernization effort include implementation of state-of-the-art data acquisition systems (including the Next Generation Weather Radar) and communications and computer processing systems. The NWS Hydrologic Service will capitalize on these systems and will incorporate results from specific hydrologic projects including collection and processing of multivariate data sets, conceptual hydrologic modeling systems, integrated hydrologic modeling systems with meteorological interfaces and automatic updating of model states, and extended streamflow prediction techniques. The salient aspects of ongoing work in these areas are highlighted in this paper, providing some perspective on the future U.S. hydrologic forecasting service and its transitional period into the 1990s.

  1. Research on forecast technology of mine gas emission based on fuzzy data mining (FDM)

    Energy Technology Data Exchange (ETDEWEB)

    Xu Chang-kai; Wang Yao-cai; Wang Jun-wei [CUMT, Xuzhou (China). School of Information and Electrical Engineering

    2004-07-01

    The safe production of coalmine can be further improved by forecasting the quantity of gas emission based on the real-time data and historical data which the gas monitoring system has saved. By making use of the advantages of data warehouse and data mining technology for processing large quantity of redundancy data, the method and its application of forecasting mine gas emission quantity based on FDM were studied. The constructing fuzzy resembling relation and clustering analysis were proposed, which the potential relationship inside the gas emission data may be found. The mode finds model and forecast model were presented, and the detailed approach to realize this forecast was also proposed, which have been applied to forecast the gas emission quantity efficiently.

  2. Extravehicular Activity (EVA) Technology Development Status and Forecast

    Science.gov (United States)

    Chullen, Cinda; Westheimer, David T.

    2010-01-01

    Beginning in Fiscal Year (FY) 2011, Extravehicular activity (EVA) technology development became a technology foundational domain under a new program Enabling Technology Development and Demonstration. The goal of the EVA technology effort is to further develop technologies that will be used to demonstrate a robust EVA system that has application for a variety of future missions including microgravity and surface EVA. Overall the objectives will be reduce system mass, reduce consumables and maintenance, increase EVA hardware robustness and life, increase crew member efficiency and autonomy, and enable rapid vehicle egress and ingress. Over the past several years, NASA realized a tremendous increase in EVA system development as part of the Exploration Technology Development Program and the Constellation Program. The evident demand for efficient and reliable EVA technologies, particularly regenerable technologies was apparent under these former programs and will continue to be needed as future mission opportunities arise. The technological need for EVA in space has been realized over the last several decades by the Gemini, Apollo, Skylab, Space Shuttle, and the International Space Station (ISS) programs. EVAs were critical to the success of these programs. Now with the ISS extension to 2028 in conjunction with a current forecasted need of at least eight EVAs per year, the EVA technology life and limited availability of the EMUs will become a critical issue eventually. The current Extravehicular Mobility Unit (EMU) has vastly served EVA demands by performing critical operations to assemble the ISS and provide repairs of satellites such as the Hubble Space Telescope. However, as the life of ISS and the vision for future mission opportunities are realized, a new EVA systems capability could be an option for the future mission applications building off of the technology development over the last several years. Besides ISS, potential mission applications include EVAs for

  3. Beating the random walk: a performance assessment of long-term interest rate forecasts

    NARCIS (Netherlands)

    den Butter, F.A.G.; Jansen, P.W.

    2013-01-01

    This article assesses the performance of a number of long-term interest rate forecast approaches, namely time series models, structural economic models, expert forecasts and combinations thereof. The predictive performance of these approaches is compared using outside sample forecast errors, where a

  4. Assessing Hourly Precipitation Forecast Skill with the Fractions Skill Score

    Science.gov (United States)

    Zhao, Bin; Zhang, Bo

    2018-02-01

    Statistical methods for category (yes/no) forecasts, such as the Threat Score, are typically used in the verification of precipitation forecasts. However, these standard methods are affected by the so-called "double-penalty" problem caused by slight displacements in either space or time with respect to the observations. Spatial techniques have recently been developed to help solve this problem. The fractions skill score (FSS), a neighborhood spatial verification method, directly compares the fractional coverage of events in windows surrounding the observations and forecasts. We applied the FSS to hourly precipitation verification by taking hourly forecast products from the GRAPES (Global/Regional Assimilation Prediction System) regional model and quantitative precipitation estimation products from the National Meteorological Information Center of China during July and August 2016, and investigated the difference between these results and those obtained with the traditional category score. We found that the model spin-up period affected the assessment of stability. Systematic errors had an insignificant role in the fraction Brier score and could be ignored. The dispersion of observations followed a diurnal cycle and the standard deviation of the forecast had a similar pattern to the reference maximum of the fraction Brier score. The coefficient of the forecasts and the observations is similar to the FSS; that is, the FSS may be a useful index that can be used to indicate correlation. Compared with the traditional skill score, the FSS has obvious advantages in distinguishing differences in precipitation time series, especially in the assessment of heavy rainfall.

  5. Assessments of Total Lightning Data Utility in Weather Forecasting

    Science.gov (United States)

    Buechler, Dennis E.; Goodman, Steve; LaCasse, Katherine; Blakeslee, Richard; Darden, Chris

    2005-01-01

    National Weather Service forecasters in Huntsville, Alabama have had access to total lightning data from the North Alabama Lightning Mapping Array (LMA) since 2003. Forecasters can monitor real-time total lightning observations on their AWIPS (Advanced Weather Interactive Processing System (AWIPS) workstations. The lightning data is used to supplement other observations such as radar and satellite data. The lightning data is updated every 2 min, providing more timely evidence of storm growth or decay than is available from 5 min radar scans. Total lightning observations have been used to positively impact warning decisions in a number of instances. A number of approaches are being pursued to assess the usefulness of total lightning measurements to the operational forecasting community in the warning decision process. These approaches, which include both qualitative and quantitative assessment methods, will be discussed. submitted to the American Meteorological Society (AMS) Conference on Meteorological Applications of Lightning Data to be held in San Diego, CA January 9-13,2005. This will be a presentation and an extended abstract will be published on a CD available from the AMS.

  6. Applying the Repertory Grid Method for Technology Forecasting: Civil Unmanned Aviation Systems for Germany

    Directory of Open Access Journals (Sweden)

    Eimecke Jörgen

    2017-09-01

    Full Text Available Multistage expert surveys like the Delphi method are proven concepts for technology forecasting that enable the prediction of content-related and temporal development in fields of innovation (e.g., [1, 2]. Advantages of these qualitative multistage methods are a simple and easy to understand concept while still delivering valid results [3]. Nevertheless, the literature also points out certain disadvantages especially in large-scale technology forecasts in particularly abstract fields of innovation [4]. The proposed approach highlights the usefulness of the repertory grid method as an alternative for technology forecasting and as a first step for preference measurement. The basic approach from Baier and Kohler [5] is modified in-so-far that an online survey reduces the cognitive burden for the experts and simplifies the data collection process. Advantages over alternative approaches through its simple structure and through combining qualitative and quantitative methods are shown and an adaption on an actual field of innovation – civil drones in Germany – is done. The measurement of a common terminology for all experts minimizes misunderstandings during the interview and the achievement of an inter-individual comparable level of abstraction is forced by the laddering technique [6] during the interview.

  7. Overview, comparative assessment and recommendations of forecasting models for short-term water demand prediction

    CSIR Research Space (South Africa)

    Anele, AO

    2017-11-01

    Full Text Available -term water demand (STWD) forecasts. In view of this, an overview of forecasting methods for STWD prediction is presented. Based on that, a comparative assessment of the performance of alternative forecasting models from the different methods is studied. Times...

  8. Review of methods for forecasting the market penetration of new technologies

    International Nuclear Information System (INIS)

    Gilshannon, S.T.; Brown, D.R.

    1996-12-01

    In 1993 the DOE Office of Energy Efficiency and Renewable Energy (EE) initiated a program called Quality Metrics. Quality Metrics was developed to measure the costs and benefits of technologies being developed by EE R ampersand D programs. The impact of any new technology is directly related to its adoption by the market. The techniques employed to project market adoption are critical to measuring a new technology's impact. Our purpose was to review current market penetration theories and models and develop a recommended approach for evaluating the market penetration of DOE technologies. The following commonly cited innovation diffusion theories were reviewed to identify analytical approaches relevant to new energy technologies: (1) the normal noncumulative adopter distribution method, (2) the Bass Model, (3) the Mansfield-Blackman Model, (4) the Fisher-Pry Model, (5) a meta-analysis of innovation diffusion studies. Of the theories reviewed, the Bass and Mansfield-Blackman models were found most applicable to forecasting the market penetration of electricity supply technologies. Their algorithms require input estimates which characterize the technology adoption behavior of the electricity supply industry. But, inadequate work has been done to quantify the technology adoption characteristics of this industry. The following energy technology market penetration models were also reviewed: (1) DOE's Renewable Energy Penetration (REP) Model, (2) DOE's Electricity Capacity Planning Submodule of the National Energy Modeling System (NEMS), (3) the Assessment of Energy Technologies (ASSET) model by Regional Economic Research, Inc., (4) the Market TREK model by the Electric Power Research Institute (EPRI). The two DOE models were developed for electricity generation technologies whereas the Regional Economic Research and EPRI models were designed for demand- side energy technology markets. Therefore, the review and evaluation focused on the DOE models

  9. Forecasting freight flows

    DEFF Research Database (Denmark)

    Lyk-Jensen, Stéphanie

    2011-01-01

    Trade patterns and transport markets are changing as a result of the growth and globalization of international trade, and forecasting future freight flow has to rely on trade forecasts. Forecasting freight flows is critical for matching infrastructure supply to demand and for assessing investment...... constitute a valuable input to freight models for forecasting future capacity problems.......Trade patterns and transport markets are changing as a result of the growth and globalization of international trade, and forecasting future freight flow has to rely on trade forecasts. Forecasting freight flows is critical for matching infrastructure supply to demand and for assessing investment...

  10. Approaches, techniques, and information technology systems in the restaurants and foodservice industry: a qualitative study in sales forecasting.

    OpenAIRE

    Green, Yvette N. J.; Weaver, Pamela A.

    2008-01-01

    This is a study of the approaches, techniques, and information technology systems utilized for restaurant sales forecasting in the full-service restaurant segment. Companies were examined using a qualitative research methods design and long interviews to gather information on approaches, techniques, and technology systems utilized in the sales forecasting process. The results of the interviews were presented along with ensuing discussion.

  11. Assessing the need for better forecasting and observability of pv

    DEFF Research Database (Denmark)

    Alet, Pierre-Jean; Efthymiou, Venizelos; Graditi, Giorgio

    2017-01-01

    In its review of the challenges and opportunities associated with massive deployment of solar PV generation, the Grid integration working group of the ETIP PV identified forecasting and observability as critical technologies for the planning and operation of the power system with large PV...... penetration. In this white paper ETIP PV set out to spell out in more details what features are needed from these technologies and what is the state of the art....

  12. Problems of Forecast

    OpenAIRE

    Kucharavy , Dmitry; De Guio , Roland

    2005-01-01

    International audience; The ability to foresee future technology is a key task of Innovative Design. The paper focuses on the obstacles to reliable prediction of technological evolution for the purpose of Innovative Design. First, a brief analysis of problems for existing forecasting methods is presented. The causes for the complexity of technology prediction are discussed in the context of reduction of the forecast errors. Second, using a contradiction analysis, a set of problems related to ...

  13. Assessment of storm forecast

    DEFF Research Database (Denmark)

    Cutululis, Nicolaos Antonio; Hahmann, Andrea N.; Huus Bjerge, Martin

    When wind speed exceeds a certain value, wind turbines shut-down in order to protect their structure. This leads to sudden wind plants shut down and to new challenges concerning the secure operation of the pan-European electric system with future large scale offshore wind power. This task aims...... stopped, completely or partially, producing due to extreme wind speeds. Wind speed and power measurements from those events are presented and compared to the forecast available at Energinet.dk. The analysis looked at wind speed and wind power forecast. The main conclusion of the analysis is that the wind...... to consider it an EWP) and that the available wind speed forecasts are given as a mean wind speed over a rather large area. At wind power level, the analysis shows that prediction of accurate production levels from a wind farm experiencing EWP is rather poor. This is partially because the power curve...

  14. The european flood alert system EFAS – Part 2: Statistical skill assessment of probabilistic and deterministic operational forecasts

    Directory of Open Access Journals (Sweden)

    J. C. Bartholmes

    2009-02-01

    Full Text Available Since 2005 the European Flood Alert System (EFAS has been producing probabilistic hydrological forecasts in pre-operational mode at the Joint Research Centre (JRC of the European Commission. EFAS aims at increasing preparedness for floods in trans-national European river basins by providing medium-range deterministic and probabilistic flood forecasting information, from 3 to 10 days in advance, to national hydro-meteorological services.

    This paper is Part 2 of a study presenting the development and skill assessment of EFAS. In Part 1, the scientific approach adopted in the development of the system has been presented, as well as its basic principles and forecast products. In the present article, two years of existing operational EFAS forecasts are statistically assessed and the skill of EFAS forecasts is analysed with several skill scores. The analysis is based on the comparison of threshold exceedances between proxy-observed and forecasted discharges. Skill is assessed both with and without taking into account the persistence of the forecasted signal during consecutive forecasts.

    Skill assessment approaches are mostly adopted from meteorology and the analysis also compares probabilistic and deterministic aspects of EFAS. Furthermore, the utility of different skill scores is discussed and their strengths and shortcomings illustrated. The analysis shows the benefit of incorporating past forecasts in the probability analysis, for medium-range forecasts, which effectively increases the skill of the forecasts.

  15. Assessing energy forecasting inaccuracy by simultaneously considering temporal and absolute errors

    International Nuclear Information System (INIS)

    Frías-Paredes, Laura; Mallor, Fermín; Gastón-Romeo, Martín; León, Teresa

    2017-01-01

    Highlights: • A new method to match time series is defined to assess energy forecasting accuracy. • This method relies in a new family of step patterns that optimizes the MAE. • A new definition of the Temporal Distortion Index between two series is provided. • A parametric extension controls both the temporal distortion index and the MAE. • Pareto optimal transformations of the forecast series are obtained for both indexes. - Abstract: Recent years have seen a growing trend in wind and solar energy generation globally and it is expected that an important percentage of total energy production comes from these energy sources. However, they present inherent variability that implies fluctuations in energy generation that are difficult to forecast. Thus, forecasting errors have a considerable role in the impacts and costs of renewable energy integration, management, and commercialization. This study presents an important advance in the task of analyzing prediction models, in particular, in the timing component of prediction error, which improves previous pioneering results. A new method to match time series is defined in order to assess energy forecasting accuracy. This method relies on a new family of step patterns, an essential component of the algorithm to evaluate the temporal distortion index (TDI). This family minimizes the mean absolute error (MAE) of the transformation with respect to the reference series (the real energy series) and also allows detailed control of the temporal distortion entailed in the prediction series. The simultaneous consideration of temporal and absolute errors allows the use of Pareto frontiers as characteristic error curves. Real examples of wind energy forecasts are used to illustrate the results.

  16. Load forecasting

    International Nuclear Information System (INIS)

    Mak, H.

    1995-01-01

    Slides used in a presentation at The Power of Change Conference in Vancouver, BC in April 1995 about the changing needs for load forecasting were presented. Technological innovations and population increase were said to be the prime driving forces behind the changing needs in load forecasting. Structural changes, market place changes, electricity supply planning changes, and changes in planning objectives were other factors discussed. It was concluded that load forecasting was a form of information gathering, that provided important market intelligence

  17. Verification of ECMWF and ECMWF/MACC's global and direct irradiance forecasts with respect to solar electricity production forecasts

    Directory of Open Access Journals (Sweden)

    M. Schroedter-Homscheidt

    2017-02-01

    Full Text Available The successful electricity grid integration of solar energy into day-ahead markets requires at least hourly resolved 48 h forecasts. Technologies as photovoltaics and non-concentrating solar thermal technologies make use of global horizontal irradiance (GHI forecasts, while all concentrating technologies both from the photovoltaic and the thermal sector require direct normal irradiances (DNI. The European Centre for Medium-Range Weather Forecasts (ECMWF has recently changed towards providing direct as well as global irradiances. Additionally, the MACC (Monitoring Atmospheric Composition & Climate near-real time services provide daily analysis and forecasts of aerosol properties in preparation of the upcoming European Copernicus programme. The operational ECMWF/IFS (Integrated Forecast System forecast system will in the medium term profit from the Copernicus service aerosol forecasts. Therefore, within the MACC‑II project specific experiment runs were performed allowing for the assessment of the performance gain of these potential future capabilities. Also the potential impact of providing forecasts with hourly output resolution compared to three-hourly resolved forecasts is investigated. The inclusion of the new aerosol climatology in October 2003 improved both the GHI and DNI forecasts remarkably, while the change towards a new radiation scheme in 2007 only had minor and partly even unfavourable impacts on the performance indicators. For GHI, larger RMSE (root mean square error values are found for broken/overcast conditions than for scattered cloud fields. For DNI, the findings are opposite with larger RMSE values for scattered clouds compared to overcast/broken cloud situations. The introduction of direct irradiances as an output parameter in the operational IFS version has not resulted in a general performance improvement with respect to biases and RMSE compared to the widely used Skartveit et al. (1998 global to direct irradiance

  18. Particle-Reinforced Aluminum Matrix Composites (AMCs—Selected Results of an Integrated Technology, User, and Market Analysis and Forecast

    Directory of Open Access Journals (Sweden)

    Anja Schmidt

    2018-02-01

    Full Text Available The research and development of new materials such as particle-reinforced aluminum matrix composites (AMCs will only result in a successful innovation if these materials show significant advantages not only from a technological, but also from an economic point of view. Against this background, in the Collaborative Research Center SFB 692, the concept of an integrated technology, user, and market analysis and forecast has been developed as a means for assessing the technological and commercial potential of new materials in early life cycle stages. After briefly describing this concept, it is applied to AMCs and the potential field of manufacturing aircraft components. Results show not only technological advances, but also considerable economic potential—the latter one primarily resulting from the possible weight reduction being enabled by the increased yield strength of the new material.

  19. Application of Medium and Seasonal Flood Forecasts for Agriculture Damage Assessment

    Science.gov (United States)

    Fakhruddin, Shamsul; Ballio, Francesco; Menoni, Scira

    2015-04-01

    Early warning is a key element for disaster risk reduction. In recent decades, major advancements have been made in medium range and seasonal flood forecasting. This progress provides a great opportunity to reduce agriculture damage and improve advisories for early action and planning for flood hazards. This approach can facilitate proactive rather than reactive management of the adverse consequences of floods. In the agricultural sector, for instance, farmers can take a diversity of options such as changing cropping patterns, applying fertilizer, irrigating and changing planting timing. An experimental medium range (1-10 day) and seasonal (20-25 days) flood forecasting model has been developed for Thailand and Bangladesh. It provides 51 sets of discharge ensemble forecasts of 1-10 days with significant persistence and high certainty and qualitative outlooks for 20-25 days. This type of forecast could assist farmers and other stakeholders for differential preparedness activities. These ensembles probabilistic flood forecasts have been customized based on user-needs for community-level application focused on agriculture system. The vulnerabilities of agriculture system were calculated based on exposure, sensitivity and adaptive capacity. Indicators for risk and vulnerability assessment were conducted through community consultations. The forecast lead time requirement, user-needs, impacts and management options for crops were identified through focus group discussions, informal interviews and community surveys. This paper illustrates potential applications of such ensembles for probabilistic medium range and seasonal flood forecasts in a way that is not commonly practiced globally today.

  20. Flood Risk Assessment and Forecasting for the Ganges-Brahmaputra-Meghna River Basins

    Science.gov (United States)

    Hopson, T. M.; Priya, S.; Young, W.; Avasthi, A.; Clayton, T. D.; Brakenridge, G. R.; Birkett, C. M.; Riddle, E. E.; Broman, D.; Boehnert, J.; Sampson, K. M.; Kettner, A.; Singh, D.

    2017-12-01

    During the 2017 South Asia monsoon, torrential rains and catastrophic floods affected more than 45 million people, including 16 million children, across the Ganges-Brahmaputra-Meghna (GBM) basins. The basin is recognized as one of the world's most disaster-prone regions, with severe floods occurring almost annually causing extreme loss of life and property. In light of this vulnerability, the World Bank and collaborators have contributed toward reducing future flood impacts through recent developments to improve operational preparedness for such events, as well as efforts in more general preparedness and resilience building through planning based on detailed risk assessments. With respect to improved event-specific flood preparedness through operational warnings, we discuss a new forecasting system that provides probability-based flood forecasts developed for more than 85 GBM locations. Forecasts are available online, along with near-real-time data maps of rainfall (predicted and actual) and river levels. The new system uses multiple data sets and multiple models to enhance forecasting skill, and provides improved forecasts up to 16 days in advance of the arrival of high waters. These longer lead times provide the opportunity to save both lives and livelihoods. With sufficient advance notice, for example, farmers can harvest a threatened rice crop or move vulnerable livestock to higher ground. Importantly, the forecasts not only predict future water levels but indicate the level of confidence in each forecast. Knowing whether the probability of a danger-level flood is 10 percent or 90 percent helps people to decide what, if any, action to take. With respect to efforts in general preparedness and resilience building, we also present a recent flood risk assessment, and how it provides, for the first time, a numbers-based view of the impacts of different size floods across the Ganges basin. The findings help identify priority areas for tackling flood risks (for

  1. Hydro-economic assessment of hydrological forecasting systems

    Science.gov (United States)

    Boucher, M.-A.; Tremblay, D.; Delorme, L.; Perreault, L.; Anctil, F.

    2012-01-01

    SummaryAn increasing number of publications show that ensemble hydrological forecasts exhibit good performance when compared to observed streamflow. Many studies also conclude that ensemble forecasts lead to a better performance than deterministic ones. This investigation takes one step further by not only comparing ensemble and deterministic forecasts to observed values, but by employing the forecasts in a stochastic decision-making assistance tool for hydroelectricity production, during a flood event on the Gatineau River in Canada. This allows the comparison between different types of forecasts according to their value in terms of energy, spillage and storage in a reservoir. The motivation for this is to adopt the point of view of an end-user, here a hydroelectricity production society. We show that ensemble forecasts exhibit excellent performances when compared to observations and are also satisfying when involved in operation management for electricity production. Further improvement in terms of productivity can be reached through the use of a simple post-processing method.

  2. Multidisciplinary studies of the social, economic and political impact resulting from recent advances in satellite meteorology. Volume 6: Executive summary. [technological forecasting spacecraft control/attitude (inclination) -classical mechanics

    Science.gov (United States)

    1975-01-01

    An assessment of the technological impact of modern satellite weather forecasting for the United States is presented. Topics discussed are: (1) television broadcasting of weather; (2) agriculture (crop production); (3) water resources; (4) urban development; (5) recreation; and (6) transportation.

  3. An improved market penetration model for wind energy technology forecasting

    International Nuclear Information System (INIS)

    Lund, P.D.

    1995-01-01

    An improved market penetration model with application to wind energy forecasting is presented. In the model, a technology diffusion model and manufacturing learning curve are combined. Based on a 85% progress ratio that was found for European wind manufactures and on wind market statistics, an additional wind power capacity of ca 4 GW is needed in Europe to reach a 30 % price reduction. A full breakthrough to low-cost utility bulk power markets could be achieved at a 24 GW level. (author)

  4. An improved market penetration model for wind energy technology forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Lund, P D [Helsinki Univ. of Technology, Espoo (Finland). Advanced Energy Systems

    1996-12-31

    An improved market penetration model with application to wind energy forecasting is presented. In the model, a technology diffusion model and manufacturing learning curve are combined. Based on a 85% progress ratio that was found for European wind manufactures and on wind market statistics, an additional wind power capacity of ca 4 GW is needed in Europe to reach a 30 % price reduction. A full breakthrough to low-cost utility bulk power markets could be achieved at a 24 GW level. (author)

  5. An improved market penetration model for wind energy technology forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Lund, P.D. [Helsinki Univ. of Technology, Espoo (Finland). Advanced Energy Systems

    1995-12-31

    An improved market penetration model with application to wind energy forecasting is presented. In the model, a technology diffusion model and manufacturing learning curve are combined. Based on a 85% progress ratio that was found for European wind manufactures and on wind market statistics, an additional wind power capacity of ca 4 GW is needed in Europe to reach a 30 % price reduction. A full breakthrough to low-cost utility bulk power markets could be achieved at a 24 GW level. (author)

  6. Fuel cycle forecasting - there are forecasts and there are forecasts

    International Nuclear Information System (INIS)

    Puechl, K.H.

    1975-01-01

    The FORECAST-NUCLEAR computer program described recognizes that forecasts are made to answer a variety of questions and, therefore, that no single forecast is universally appropriate. Also, it recognizes that no two individuals will completely agree as to the input data that are appropriate for obtaining an answer to even a single simple question. Accordingly, the program was written from a utilitarian standpoint: it allows working with multiple projections; data inputting is simple to allow game-playing; computation time is short to minimize the cost of 'what if' assessements; and detail is internally carried to allow meaningful analysis. (author)

  7. Fuel cycle forecasting - there are forecasts and there are forecasts

    Energy Technology Data Exchange (ETDEWEB)

    Puechl, K H

    1975-12-01

    The FORECAST-NUCLEAR computer program described recognizes that forecasts are made to answer a variety of questions and, therefore, that no single forecast is universally appropriate. Also, it recognizes that no two individuals will completely agree as to the input data that are appropriate for obtaining an answer to even a single simple question. Accordingly, the program was written from a utilitarian standpoint: it allows working with multiple projections; data inputting is simple to allow game-playing; computation time is short to minimize the cost of 'what if' assessements; and detail is internally carried to allow meaningful analysis.

  8. Moving beyond the cost-loss ratio: economic assessment of streamflow forecasts for a risk-averse decision maker

    Science.gov (United States)

    Matte, Simon; Boucher, Marie-Amélie; Boucher, Vincent; Fortier Filion, Thomas-Charles

    2017-06-01

    A large effort has been made over the past 10 years to promote the operational use of probabilistic or ensemble streamflow forecasts. Numerous studies have shown that ensemble forecasts are of higher quality than deterministic ones. Many studies also conclude that decisions based on ensemble rather than deterministic forecasts lead to better decisions in the context of flood mitigation. Hence, it is believed that ensemble forecasts possess a greater economic and social value for both decision makers and the general population. However, the vast majority of, if not all, existing hydro-economic studies rely on a cost-loss ratio framework that assumes a risk-neutral decision maker. To overcome this important flaw, this study borrows from economics and evaluates the economic value of early warning flood systems using the well-known Constant Absolute Risk Aversion (CARA) utility function, which explicitly accounts for the level of risk aversion of the decision maker. This new framework allows for the full exploitation of the information related to a forecasts' uncertainty, making it especially suited for the economic assessment of ensemble or probabilistic forecasts. Rather than comparing deterministic and ensemble forecasts, this study focuses on comparing different types of ensemble forecasts. There are multiple ways of assessing and representing forecast uncertainty. Consequently, there exist many different means of building an ensemble forecasting system for future streamflow. One such possibility is to dress deterministic forecasts using the statistics of past error forecasts. Such dressing methods are popular among operational agencies because of their simplicity and intuitiveness. Another approach is the use of ensemble meteorological forecasts for precipitation and temperature, which are then provided as inputs to one or many hydrological model(s). In this study, three concurrent ensemble streamflow forecasting systems are compared: simple statistically dressed

  9. Integral assessment of floodplains as a basis for spatially-explicit flood loss forecasts

    Science.gov (United States)

    Zischg, Andreas Paul; Mosimann, Markus; Weingartner, Rolf

    2016-04-01

    flood scenario, the resulting number of affected residents, houses and therefore the losses are computed. This integral assessment leads to a hydro-economical characterisation of each floodplain. Based on that, a transfer function between discharge forecast and damages can be elaborated. This transfer function describes the relationship between predicted peak discharge, flood volume and the number of exposed houses, residents and the related losses. It also can be used to downscale the regional discharge forecast to a local level loss forecast. In addition, a dynamic map delimiting the probable flooded areas on the basis of the forecasted discharge can be prepared. The predicted losses and the delimited flooded areas provide a complementary information for assessing the need of preventive measures on one hand on the long-term timescale and on the other hand 6h-24h in advance of a predicted flood. To conclude, we can state that the transfer function offers the possibility for an integral assessment of floodplains as a basis for spatially-explicit flood loss forecasts. The procedure has been developed and tested in the alpine and pre-alpine environment of the Aare river catchment upstream of Bern, Switzerland.

  10. Transition, Training, and Assessment of Multispectral Composite Imagery in Support of the NWS Aviation Forecast Mission

    Science.gov (United States)

    Fuell, Kevin; Jedlovec, Gary; Leroy, Anita; Schultz, Lori

    2015-01-01

    The NASA/Short-term Prediction, Research, and Transition (SPoRT) Program works closely with NOAA/NWS weather forecasters to transition unique satellite data and capabilities into operations in order to assist with nowcasting and short-term forecasting issues. Several multispectral composite imagery (i.e. RGB) products were introduced to users in the early 2000s to support hydrometeorology and aviation challenges as well as incident support. These activities lead to SPoRT collaboration with the GOES-R Proving Ground efforts where instruments such as MODIS (Aqua, Terra) and S-NPP/VIIRS imagers began to be used as near-realtime proxies to future capabilities of the Advanced Baseline Imager (ABI). One of the composite imagery products introduced to users was the Night-time Microphysics RGB, originally developed by EUMETSAT. SPoRT worked to transition this imagery to NWS users, provide region-specific training, and assess the impact of the imagery to aviation forecast needs. This presentation discusses the method used to interact with users to address specific aviation forecast challenges, including training activities undertaken to prepare for a product assessment. Users who assessed the multispectral imagery ranged from southern U.S. inland and coastal NWS weather forecast offices (WFOs), to those in the Rocky Mountain Front Range region and West Coast, as well as highlatitude forecasters of Alaska. These user-based assessments were documented and shared with the satellite community to support product developers and the broad users of new generation satellite data.

  11. A quality assessment of the MARS crop yield forecasting system for the European Union

    Science.gov (United States)

    van der Velde, Marijn; Bareuth, Bettina

    2015-04-01

    Timely information on crop production forecasts can become of increasing importance as commodity markets are more and more interconnected. Impacts across large crop production areas due to (e.g.) extreme weather and pest outbreaks can create ripple effects that may affect food prices and availability elsewhere. The MARS Unit (Monitoring Agricultural ResourceS), DG Joint Research Centre, European Commission, has been providing forecasts of European crop production levels since 1993. The operational crop production forecasting is carried out with the MARS Crop Yield Forecasting System (M-CYFS). The M-CYFS is used to monitor crop growth development, evaluate short-term effects of anomalous meteorological events, and provide monthly forecasts of crop yield at national and European Union level. The crop production forecasts are published in the so-called MARS bulletins. Forecasting crop yield over large areas in the operational context requires quality benchmarks. Here we present an analysis of the accuracy and skill of past crop yield forecasts of the main crops (e.g. soft wheat, grain maize), throughout the growing season, and specifically for the final forecast before harvest. Two simple benchmarks to assess the skill of the forecasts were defined as comparing the forecasts to 1) a forecast equal to the average yield and 2) a forecast using a linear trend established through the crop yield time-series. These reveal a variability in performance as a function of crop and Member State. In terms of production, the yield forecasts of 67% of the EU-28 soft wheat production and 80% of the EU-28 maize production have been forecast superior to both benchmarks during the 1993-2013 period. In a changing and increasingly variable climate crop yield forecasts can become increasingly valuable - provided they are used wisely. We end our presentation by discussing research activities that could contribute to this goal.

  12. Assessing Variability and Errors in Historical Runoff Forecasting with Physical Models and Alternative Data Sources

    Science.gov (United States)

    Penn, C. A.; Clow, D. W.; Sexstone, G. A.

    2017-12-01

    Water supply forecasts are an important tool for water resource managers in areas where surface water is relied on for irrigating agricultural lands and for municipal water supplies. Forecast errors, which correspond to inaccurate predictions of total surface water volume, can lead to mis-allocated water and productivity loss, thus costing stakeholders millions of dollars. The objective of this investigation is to provide water resource managers with an improved understanding of factors contributing to forecast error, and to help increase the accuracy of future forecasts. In many watersheds of the western United States, snowmelt contributes 50-75% of annual surface water flow and controls both the timing and volume of peak flow. Water supply forecasts from the Natural Resources Conservation Service (NRCS), National Weather Service, and similar cooperators use precipitation and snowpack measurements to provide water resource managers with an estimate of seasonal runoff volume. The accuracy of these forecasts can be limited by available snowpack and meteorological data. In the headwaters of the Rio Grande, NRCS produces January through June monthly Water Supply Outlook Reports. This study evaluates the accuracy of these forecasts since 1990, and examines what factors may contribute to forecast error. The Rio Grande headwaters has experienced recent changes in land cover from bark beetle infestation and a large wildfire, which can affect hydrological processes within the watershed. To investigate trends and possible contributing factors in forecast error, a semi-distributed hydrological model was calibrated and run to simulate daily streamflow for the period 1990-2015. Annual and seasonal watershed and sub-watershed water balance properties were compared with seasonal water supply forecasts. Gridded meteorological datasets were used to assess changes in the timing and volume of spring precipitation events that may contribute to forecast error. Additionally, a

  13. Utilizing Operational and Improved Remote Sensing Measurements to Assess Air Quality Monitoring Model Forecasts

    Science.gov (United States)

    Gan, Chuen-Meei

    Air quality model forecasts from Weather Research and Forecast (WRF) and Community Multiscale Air Quality (CMAQ) are often used to support air quality applications such as regulatory issues and scientific inquiries on atmospheric science processes. In urban environments, these models become more complex due to the inherent complexity of the land surface coupling and the enhanced pollutants emissions. This makes it very difficult to diagnose the model, if the surface parameter forecasts such as PM2.5 (particulate matter with aerodynamic diameter less than 2.5 microm) are not accurate. For this reason, getting accurate boundary layer dynamic forecasts is as essential as quantifying realistic pollutants emissions. In this thesis, we explore the usefulness of vertical sounding measurements on assessing meteorological and air quality forecast models. In particular, we focus on assessing the WRF model (12km x 12km) coupled with the CMAQ model for the urban New York City (NYC) area using multiple vertical profiling and column integrated remote sensing measurements. This assessment is helpful in probing the root causes for WRF-CMAQ overestimates of surface PM2.5 occurring both predawn and post-sunset in the NYC area during the summer. In particular, we find that the significant underestimates in the WRF PBL height forecast is a key factor in explaining this anomaly. On the other hand, the model predictions of the PBL height during daytime when convective heating dominates were found to be highly correlated to lidar derived PBL height with minimal bias. Additional topics covered in this thesis include mathematical method using direct Mie scattering approach to convert aerosol microphysical properties from CMAQ into optical parameters making direct comparisons with lidar and multispectral radiometers feasible. Finally, we explore some tentative ideas on combining visible (VIS) and mid-infrared (MIR) sensors to better separate aerosols into fine and coarse modes.

  14. An assessment of the ECMWF tropical cyclone ensemble forecasting system and its use for insurance loss predictions

    Science.gov (United States)

    Aemisegger, F.; Martius, O.; Wüest, M.

    2010-09-01

    Tropical cyclones (TC) are amongst the most impressive and destructive weather systems of Earth's atmosphere. The costs related to such intense natural disasters have been rising in recent years and may potentially continue to increase in the near future due to changes in magnitude, timing, duration or location of tropical storms. This is a challenging situation for numerical weather prediction, which should provide a decision basis for short term protective measures through high quality medium range forecasts on the one hand. On the other hand, the insurance system bears great responsibility in elaborating proactive plans in order to face these extreme events that individuals cannot manage independently. Real-time prediction and early warning systems are needed in the insurance sector in order to face an imminent hazard and minimise losses. Early loss estimates are important in order to allocate capital and to communicate to investors. The ECMWF TC identification algorithm delivers information on the track and intensity of storms based on the ensemble forecasting system. This provides a physically based framework to assess the uncertainty in the forecast of a specific event. The performance of the ECMWF TC ensemble forecasts is evaluated in terms of cyclone intensity and location in this study and the value of such a physically-based quantification of uncertainty in the meteorological forecast for the estimation of insurance losses is assessed. An evaluation of track and intensity forecasts of hurricanes in the North Atlantic during the years 2005 to 2009 is carried out. Various effects are studied like the differences in forecasts over land or sea, as well as links between storm intensity and forecast error statistics. The value of the ECMWF TC forecasting system for the global re-insurer Swiss Re was assessed by performing insurance loss predictions using their in-house loss model for several case studies of particularly devastating events. The generally known

  15. An Assessment of the Subseasonal Forecast Performance in the Extended Global Ensemble Forecast System (GEFS)

    Science.gov (United States)

    Sinsky, E.; Zhu, Y.; Li, W.; Guan, H.; Melhauser, C.

    2017-12-01

    Optimal forecast quality is crucial for the preservation of life and property. Improving monthly forecast performance over both the tropics and extra-tropics requires attention to various physical aspects such as the representation of the underlying SST, model physics and the representation of the model physics uncertainty for an ensemble forecast system. This work focuses on the impact of stochastic physics, SST and the convection scheme on forecast performance for the sub-seasonal scale over the tropics and extra-tropics with emphasis on the Madden-Julian Oscillation (MJO). A 2-year period is evaluated using the National Centers for Environmental Prediction (NCEP) Global Ensemble Forecast System (GEFS). Three experiments with different configurations than the operational GEFS were performed to illustrate the impact of the stochastic physics, SST and convection scheme. These experiments are compared against a control experiment (CTL) which consists of the operational GEFS but its integration is extended from 16 to 35 days. The three configurations are: 1) SPs, which uses a Stochastically Perturbed Physics Tendencies (SPPT), Stochastic Perturbed Humidity (SHUM) and Stochastic Kinetic Energy Backscatter (SKEB); 2) SPs+SST_bc, which uses a combination of SPs and a bias-corrected forecast SST from the NCEP Climate Forecast System Version 2 (CFSv2); and 3) SPs+SST_bc+SA_CV, which combines SPs, a bias-corrected forecast SST and a scale aware convection scheme. When comparing to the CTL experiment, SPs shows substantial improvement. The MJO skill has improved by about 4 lead days during the 2-year period. Improvement is also seen over the extra-tropics due to the updated stochastic physics, where there is a 3.1% and a 4.2% improvement during weeks 3 and 4 over the northern hemisphere and southern hemisphere, respectively. Improvement is also seen when the bias-corrected CFSv2 SST is combined with SPs. Additionally, forecast performance enhances when the scale aware

  16. A GM (1, 1) Markov Chain-Based Aeroengine Performance Degradation Forecast Approach Using Exhaust Gas Temperature

    OpenAIRE

    Zhao, Ning-bo; Yang, Jia-long; Li, Shu-ying; Sun, Yue-wu

    2014-01-01

    Performance degradation forecast technology for quantitatively assessing degradation states of aeroengine using exhaust gas temperature is an important technology in the aeroengine health management. In this paper, a GM (1, 1) Markov chain-based approach is introduced to forecast exhaust gas temperature by taking the advantages of GM (1, 1) model in time series and the advantages of Markov chain model in dealing with highly nonlinear and stochastic data caused by uncertain factors. In this ap...

  17. Assessment of marine weather forecasts over the Indian sector of Southern Ocean

    Science.gov (United States)

    Gera, Anitha; Mahapatra, D. K.; Sharma, Kuldeep; Prakash, Satya; Mitra, A. K.; Iyengar, G. R.; Rajagopal, E. N.; Anilkumar, N.

    2017-09-01

    The Southern Ocean (SO) is one of the important regions where significant processes and feedbacks of the Earth's climate take place. Expeditions to the SO provide useful data for improving global weather/climate simulations and understanding many processes. Some of the uncertainties in these weather/climate models arise during the first few days of simulation/forecast and do not grow much further. NCMRWF issued real-time five day weather forecasts of mean sea level pressure, surface winds, winds at 500 hPa & 850 hPa and rainfall, daily to NCAOR to provide guidance for their expedition to Indian sector of SO during the austral summer of 2014-2015. Evaluation of the skill of these forecasts indicates possible error growth in the atmospheric model at shorter time scales. The error growth is assessed using the model analysis/reanalysis, satellite data and observations made during the expedition. The observed variability of sub-seasonal rainfall associated with mid-latitude systems is seen to exhibit eastward propagations and are well reproduced in the model forecasts. All cyclonic disturbances including the sub-polar lows and tropical cyclones that occurred during this period were well captured in the model forecasts. Overall, this model performs reasonably well over the Indian sector of the SO in medium range time scale.

  18. A Time Series Model for Assessing the Trend and Forecasting the Road Traffic Accident Mortality.

    Science.gov (United States)

    Yousefzadeh-Chabok, Shahrokh; Ranjbar-Taklimie, Fatemeh; Malekpouri, Reza; Razzaghi, Alireza

    2016-09-01

    Road traffic accident (RTA) is one of the main causes of trauma and known as a growing public health concern worldwide, especially in developing countries. Assessing the trend of fatalities in the past years and forecasting it enables us to make the appropriate planning for prevention and control. This study aimed to assess the trend of RTAs and forecast it in the next years by using time series modeling. In this historical analytical study, the RTA mortalities in Zanjan Province, Iran, were evaluated during 2007 - 2013. The time series analyses including Box-Jenkins models were used to assess the trend of accident fatalities in previous years and forecast it for the next 4 years. The mean age of the victims was 37.22 years (SD = 20.01). From a total of 2571 deaths, 77.5% (n = 1992) were males and 22.5% (n = 579) were females. The study models showed a descending trend of fatalities in the study years. The SARIMA (1, 1, 3) (0, 1, 0) 12 model was recognized as a best fit model in forecasting the trend of fatalities. Forecasting model also showed a descending trend of traffic accident mortalities in the next 4 years. There was a decreasing trend in the study and the future years. It seems that implementation of some interventions in the recent decade has had a positive effect on the decline of RTA fatalities. Nevertheless, there is still a need to pay more attention in order to prevent the occurrence and the mortalities related to traffic accidents.

  19. Quadrennial Technology Review 2015: Technology Assessments--Marine and Hydrokinetic Power

    Energy Technology Data Exchange (ETDEWEB)

    Sam Baldwin, Gilbert Bindewald, Austin Brown, Charles Chen, Kerry Cheung, Corrie Clark, Joe Cresko,

    2015-10-07

    Marine and hydrokinetic (MHK) technologies convert the energy of waves, tides, and river and ocean currents into electricity. With more than 50% of the U.S. population living within 50 miles of the nation’s coasts, MHK technologies hold significant potential to supply renewable electricity to consumers in coastal load centers, particularly in the near term in areas with high costs of electricity and longer term in high resource areas in close proximity to major coastal load centers. MHK resource assessments identify a total U.S. technical resource potential of approximately 1250–1850 terawatt-hours (TWh) of generation per year from ocean wave, ocean current, ocean tidal, and river current energy. Of this, the U.S. continental technical resource potential is approximately 500–750 TWh/year. For context, roughly 90,000 homes can be powered by 1 TWh of electricity generation each year. A cost-effective MHK industry could provide a substantial amount of electricity for the nation owing in large part to its unique advantages as a source of energy, including its vast resource potential, its close proximity to major coastal load centers, and its long-term predictability and near-term forecastability.

  20. Foresight and Forecasts

    DEFF Research Database (Denmark)

    Kilbourn, Kyle; Bay, Marie Brøndum

    In predicting areas of growth, public innovation projects may rely on optimistic visions of technology still in development as a way of ensuring novelty for funding. This paper explores what happens when forecasts of robotic technology meets the practice of sterile supply in a preliminary stage...

  1. A national framework for flood forecasting model assessment for use in operations and investment planning over England and Wales

    Science.gov (United States)

    Moore, Robert J.; Wells, Steven C.; Cole, Steven J.

    2016-04-01

    It has been common for flood forecasting systems to be commissioned at a catchment or regional level in response to local priorities and hydrological conditions, leading to variety in system design and model choice. As systems mature and efficiencies of national management are sought, there can be a drive towards system rationalisation, gaining an overview of model performance and consideration of simplification through model-type convergence. Flood forecasting model assessments, whilst overseen at a national level, may be commissioned and managed at a catchment and regional level, take a variety of forms and be large in number. This presents a challenge when an integrated national assessment is required to guide operational use of flood forecasts and plan future investment in flood forecasting models and supporting hydrometric monitoring. This contribution reports on how a nationally consistent framework for flood forecasting model performance has been developed to embrace many past, ongoing and future assessments for local river systems by engineering consultants across England & Wales. The outcome is a Performance Summary for every site model assessed which, on a single page, contains relevant catchment information for context, a selection of overlain forecast and observed hydrographs and a set of performance statistics with associated displays of novel condensed form. One display provides performance comparison with other models that may exist for the site. The performance statistics include skill scores for forecasting events (flow/level threshold crossings) of differing severity/rarity, indicating their probability and likely timing, which have real value in an operational setting. The local models assessed can be of any type and span rainfall-runoff (conceptual and transfer function) and flow routing (hydrological and hydrodynamic) forms. Also accommodated by the framework is the national G2G (Grid-to-Grid) distributed hydrological model, providing area

  2. Forecasts: uncertain, inaccurate and biased?

    DEFF Research Database (Denmark)

    Nicolaisen, Morten Skou; Ambrasaite, Inga; Salling, Kim Bang

    2012-01-01

    Cost Benefit Analysis (CBA) is the dominating methodology for appraisal of transport infrastructure projects across the globe. In order to adequately assess the costs and benefits of such projects two types of forecasts are crucial to the validity of the appraisal. First are the forecasts of cons....... It is recommended that more attention is given to monitoring completed projects so future forecasts can benefit from better data availability through systematic ex-post evaluations, and an example of how to utilize such data in practice is presented.......Cost Benefit Analysis (CBA) is the dominating methodology for appraisal of transport infrastructure projects across the globe. In order to adequately assess the costs and benefits of such projects two types of forecasts are crucial to the validity of the appraisal. First are the forecasts...... of construction costs, which account for the majority of total project costs. Second are the forecasts of travel time savings, which account for the majority of total project benefits. The latter of these is, inter alia, determined by forecasts of travel demand, which we shall use as a proxy for the forecasting...

  3. Assessing the Skill of Chlorophyll Forecasts: Latest Development and Challenges Ahead Using the Case of the Equatorial Pacific

    Science.gov (United States)

    Rousseaux, Cecile S.; Gregg, Watson W.

    2018-01-01

    Using a global ocean biogeochemical model combined with a forecast of physical oceanic and atmospheric variables from the NASA Global Modeling and Assimilation Office, we assess the skill of a chlorophyll concentrations forecast in the Equatorial Pacific for the period 2012-2015 with a focus on the forecast of the onset of the 2015 El Nino event. Using a series of retrospective 9-month hindcasts, we assess the uncertainties of the forecasted chlorophyll by comparing the monthly total chlorophyll concentration from the forecast with the corresponding monthly ocean chlorophyll data from the Suomi-National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (S-NPP VIIRS) satellite. The forecast was able to reproduce the phasing of the variability in chlorophyll concentration in the Equatorial Pacific, including the beginning of the 2015-2016 El Nino. The anomaly correlation coefficient (ACC) was significant (p less than 0.05) for forecast at 1-month (R=0.33), 8-month (R=0.42) and 9-month (R=0.41) lead times. The root mean square error (RMSE) increased from 0.0399 microgram chl L(exp -1) for the 1-month lead forecast to a maximum of 0.0472 microgram chl L(exp -1) for the 9-month lead forecast indicating that the forecast of the amplitude of chlorophyll concentration variability was getting worse. Forecasts with a 3-month lead time were on average the closest to the S-NPP VIIRS data (23% or 0.033 microgram chl L(exp -1)) while the forecast with a 9-month lead time were the furthest (31% or 0.042 microgram chl L(exp -1)). These results indicate the potential for forecasting chlorophyll concentration in this region but also highlights various deficiencies and suggestions for improvements to the current biogeochemical forecasting system. This system provides an initial basis for future applications including the effects of El Nino events on fisheries and other ocean resources given improvements identified in the analysis of these results.

  4. A Time Series Model for Assessing the Trend and Forecasting the Road Traffic Accident Mortality

    Science.gov (United States)

    Yousefzadeh-Chabok, Shahrokh; Ranjbar-Taklimie, Fatemeh; Malekpouri, Reza; Razzaghi, Alireza

    2016-01-01

    Background Road traffic accident (RTA) is one of the main causes of trauma and known as a growing public health concern worldwide, especially in developing countries. Assessing the trend of fatalities in the past years and forecasting it enables us to make the appropriate planning for prevention and control. Objectives This study aimed to assess the trend of RTAs and forecast it in the next years by using time series modeling. Materials and Methods In this historical analytical study, the RTA mortalities in Zanjan Province, Iran, were evaluated during 2007 - 2013. The time series analyses including Box-Jenkins models were used to assess the trend of accident fatalities in previous years and forecast it for the next 4 years. Results The mean age of the victims was 37.22 years (SD = 20.01). From a total of 2571 deaths, 77.5% (n = 1992) were males and 22.5% (n = 579) were females. The study models showed a descending trend of fatalities in the study years. The SARIMA (1, 1, 3) (0, 1, 0) 12 model was recognized as a best fit model in forecasting the trend of fatalities. Forecasting model also showed a descending trend of traffic accident mortalities in the next 4 years. Conclusions There was a decreasing trend in the study and the future years. It seems that implementation of some interventions in the recent decade has had a positive effect on the decline of RTA fatalities. Nevertheless, there is still a need to pay more attention in order to prevent the occurrence and the mortalities related to traffic accidents. PMID:27800467

  5. The AviaDem forecasting model: illustration of a forecasting case at Amsterdam Schiphol Airport

    NARCIS (Netherlands)

    Veldhuis, J.; Lieshout, R.

    2010-01-01

    The paper describes an aviation market forecasting model which focuses on market forecasts for airports. Most forecasting models in use today assess aviation trends resulting from macroeconomic trends. The model described in this paper has this feature built in, but the added value of this model is

  6. A GM (1, 1 Markov Chain-Based Aeroengine Performance Degradation Forecast Approach Using Exhaust Gas Temperature

    Directory of Open Access Journals (Sweden)

    Ning-bo Zhao

    2014-01-01

    Full Text Available Performance degradation forecast technology for quantitatively assessing degradation states of aeroengine using exhaust gas temperature is an important technology in the aeroengine health management. In this paper, a GM (1, 1 Markov chain-based approach is introduced to forecast exhaust gas temperature by taking the advantages of GM (1, 1 model in time series and the advantages of Markov chain model in dealing with highly nonlinear and stochastic data caused by uncertain factors. In this approach, firstly, the GM (1, 1 model is used to forecast the trend by using limited data samples. Then, Markov chain model is integrated into GM (1, 1 model in order to enhance the forecast performance, which can solve the influence of random fluctuation data on forecasting accuracy and achieving an accurate estimate of the nonlinear forecast. As an example, the historical monitoring data of exhaust gas temperature from CFM56 aeroengine of China Southern is used to verify the forecast performance of the GM (1, 1 Markov chain model. The results show that the GM (1, 1 Markov chain model is able to forecast exhaust gas temperature accurately, which can effectively reflect the random fluctuation characteristics of exhaust gas temperature changes over time.

  7. Probabilistic Latent Semantic Analyses (PLSA in Bibliometric Analysis for Technology Forecasting

    Directory of Open Access Journals (Sweden)

    Wang Zan

    2007-03-01

    Full Text Available Due to the availability of internet-based abstract services and patent databases, bibliometric analysis has become one of key technology forecasting approaches. Recently, latent semantic analysis (LSA has been applied to improve the accuracy in document clustering. In this paper, a new LSA method, probabilistic latent semantic analysis (PLSA which uses probabilistic methods and algebra to search latent space in the corpus is further applied in document clustering. The results show that PLSA is more accurate than LSA and the improved iteration method proposed by authors can simplify the computing process and improve the computing efficiency

  8. Forecast Informed Reservoir Operations: Bringing Science and Decision-Makers Together to Explore Use of Hydrometeorological Forecasts to Support Future Reservoir Operations

    Science.gov (United States)

    Ralph, F. M.; Jasperse, J.

    2017-12-01

    Forecast Informed Reservoir Operations (FIRO) is a proposed strategy that is exploring inorporation of improved hydrometeorological forecasts of land-falling atmospheric rivers on the U.S. West Coast into reservoir operations. The first testbed for this strategy is Lake Mendocino, which is located in the East Fork of the 1485 mi2 Russian River Watershed in northern California. This project is guided by the Lake Mendocino FIRO Steering Committee (SC). The SC is an ad hoc committee that consists of water managers and scientists from several federal, state, and local agencies, and universities who have teamed to evaluate whether current or improved technology and scientific understanding can be utilized to improve water supply reliability, enhance flood mitigation and support recovery of listed salmon for the Russian River of northern California. In 2015, the SC created a detailed work plan, which included a Preliminary Viability Assessment, which has now been completed. The SC developed a vision that operational efficiency would be improved by using forecasts to inform decisions about releasing or storing water. FIRO would use available reservoir storage in an efficient manner by (1) better forecasting inflow (or lack of inflow) with enhanced technology, and (2) adapting operation in real time to meet the need for storage, rather than making storage available just in case it is needed. The envisioned FIRO strategy has the potential to simultaneously improve water supply reliability, flood protection, and ecosystem outcomes through a more efficient use of existing infrastructure while requiring minimal capital improvements in the physical structure of the dam. This presentation will provide an overview of the creation of the FIRO SC and how it operates, and describes the lessons learned through this partnership. Results in the FIRO Preliminary Viability Assessment will be summarized and next steps described.

  9. Developing integrated performance assessment and forecasting the level of financial and economic enterprise stability

    Directory of Open Access Journals (Sweden)

    Khudyakova T.A.

    2017-01-01

    Full Text Available The article deals with the problem of assessing and forecasting the level of financial and economic enterprise stability through the integrated indicators development. Currently, many enterprises operate under variable external environment, which imposes a strict requirement to consider this uncertainty. For the evaluation, analysis and prediction of the sustainability of the enterprise in the conditions of crisis we believe it possible and necessary to use the apparatus of probability theory and mathematical statistics. This problem solution will improve quantitative assessing the financial and economic stability level, forecasting possible scenarios of the enterprise development and, therefore, based on the proactive management principles and adaptation processes will greatly increase their effective functioning, as well as reduce bankruptcy probability.

  10. Short-term residential load forecasting: Impact of calendar effects and forecast granularity

    DEFF Research Database (Denmark)

    Lusis, Peter; Khalilpour, Kaveh Rajab; Andrew, Lachlan

    2017-01-01

    forecasting for a single-customer or even down at an appliance level. Access to high resolution data from smart meters has enabled the research community to assess conventional load forecasting techniques and develop new forecasting strategies suitable for demand-side disaggregated loads. This paper studies...... how calendar effects, forecasting granularity and the length of the training set affect the accuracy of a day-ahead load forecast for residential customers. Root mean square error (RMSE) and normalized RMSE were used as forecast error metrics. Regression trees, neural networks, and support vector...... regression yielded similar average RMSE results, but statistical analysis showed that regression trees technique is significantly better. The use of historical load profiles with daily and weekly seasonality, combined with weather data, leaves the explicit calendar effects a very low predictive power...

  11. Exploring the interactions between forecast accuracy, risk perception and perceived forecast reliability in reservoir operator's decision to use forecast

    Science.gov (United States)

    Shafiee-Jood, M.; Cai, X.

    2017-12-01

    Advances in streamflow forecasts at different time scales offer a promise for proactive flood management and improved risk management. Despite the huge potential, previous studies have found that water resources managers are often not willing to incorporate streamflow forecasts information in decisions making, particularly in risky situations. While low accuracy of forecasts information is often cited as the main reason, some studies have found that implementation of streamflow forecasts sometimes is impeded by institutional obstacles and behavioral factors (e.g., risk perception). In fact, a seminal study by O'Connor et al. (2005) found that risk perception is the strongest determinant of forecast use while managers' perception about forecast reliability is not significant. In this study, we aim to address this issue again. However, instead of using survey data and regression analysis, we develop a theoretical framework to assess the user-perceived value of streamflow forecasts. The framework includes a novel behavioral component which incorporates both risk perception and perceived forecast reliability. The framework is then used in a hypothetical problem where reservoir operator should react to probabilistic flood forecasts with different reliabilities. The framework will allow us to explore the interactions among risk perception and perceived forecast reliability, and among the behavioral components and information accuracy. The findings will provide insights to improve the usability of flood forecasts information through better communication and education.

  12. Technology assessment, expectations and networks : An illustration using new materials

    NARCIS (Netherlands)

    Den Hond, Frank; Groenewegen, Peter; Vergragt, Philip

    1990-01-01

    This presents an approach to forecasting and identifying the positive and negative consequences of a new technology. It outlines aspects of the theory of actor networks, and shows how it can help the analysis. As a specific example, to aid communication, it considers new materials technology

  13. Quantile forecast discrimination ability and value

    DEFF Research Database (Denmark)

    Ben Bouallègue, Zied; Pinson, Pierre; Friederichs, Petra

    2015-01-01

    While probabilistic forecast verification for categorical forecasts is well established, some of the existing concepts and methods have not found their equivalent for the case of continuous variables. New tools dedicated to the assessment of forecast discrimination ability and forecast value are ...... is illustrated based on synthetic datasets, as well as for the case of global radiation forecasts from the high resolution ensemble COSMO-DE-EPS of the German Weather Service....

  14. Skill assessment of the coupled physical-biogeochemical operational Mediterranean Forecasting System

    Science.gov (United States)

    Cossarini, Gianpiero; Clementi, Emanuela; Salon, Stefano; Grandi, Alessandro; Bolzon, Giorgio; Solidoro, Cosimo

    2016-04-01

    The Mediterranean Monitoring and Forecasting Centre (Med-MFC) is one of the regional production centres of the European Marine Environment Monitoring Service (CMEMS-Copernicus). Med-MFC operatively manages a suite of numerical model systems (3DVAR-NEMO-WW3 and 3DVAR-OGSTM-BFM) that provides gridded datasets of physical and biogeochemical variables for the Mediterranean marine environment with a horizontal resolution of about 6.5 km. At the present stage, the operational Med-MFC produces ten-day forecast: daily for physical parameters and bi-weekly for biogeochemical variables. The validation of the coupled model system and the estimate of the accuracy of model products are key issues to ensure reliable information to the users and the downstream services. Product quality activities at Med-MFC consist of two levels of validation and skill analysis procedures. Pre-operational qualification activities focus on testing the improvement of the quality of a new release of the model system and relays on past simulation and historical data. Then, near real time (NRT) validation activities aim at the routinely and on-line skill assessment of the model forecast and relays on the NRT available observations. Med-MFC validation framework uses both independent (i.e. Bio-Argo float data, in-situ mooring and vessel data of oxygen, nutrients and chlorophyll, moored buoys, tide-gauges and ADCP of temperature, salinity, sea level and velocity) and semi-independent data (i.e. data already used for assimilation, such as satellite chlorophyll, Satellite SLA and SST and in situ vertical profiles of temperature and salinity from XBT, Argo and Gliders) We give evidence that different variables (e.g. CMEMS-products) can be validated at different levels (i.e. at the forecast level or at the level of model consistency) and at different spatial and temporal scales. The fundamental physical parameters temperature, salinity and sea level are routinely validated on daily, weekly and quarterly base

  15. New technology for using meteorological information in forest insect pest forecast and warning systems.

    Science.gov (United States)

    Qin, Jiang-Lin; Yang, Xiu-Hao; Yang, Zhong-Wu; Luo, Ji-Tong; Lei, Xiu-Feng

    2017-12-01

    Near surface air temperature and rainfall are major weather factors affecting forest insect dynamics. The recent developments in remote sensing retrieval and geographic information system spatial analysis techniques enable the utilization of weather factors to significantly enhance forest pest forecasting and warning systems. The current study focused on building forest pest digital data structures as a platform of correlation analysis between weather conditions and forest pest dynamics for better pest forecasting and warning systems using the new technologies. The study dataset contained 3 353 425 small polygons with 174 defined attributes covering 95 counties of Guangxi province of China currently registering 292 forest pest species. Field data acquisition and information transfer systems were established with four software licences that provided 15-fold improvement compared to the systems currently used in China. Nine technical specifications were established including codes of forest districts, pest species and host tree species, and standard practices of forest pest monitoring and information management. Attributes can easily be searched using ArcGIS9.3 and/or the free QGIS2.16 software. Small polygons with pest relevant attributes are a new tool of precision farming and detailed forest insect pest management that are technologically advanced. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

  16. Analysing UK real estate market forecast disagreement

    OpenAIRE

    McAllister, Patrick; Newell, G.; Matysiak, George

    2005-01-01

    Given the significance of forecasting in real estate investment decisions, this paper investigates forecast uncertainty and disagreement in real estate market forecasts. Using the Investment Property Forum (IPF) quarterly survey amongst UK independent real estate forecasters, these real estate forecasts are compared with actual real estate performance to assess a number of real estate forecasting issues in the UK over 1999-2004, including real estate forecast error, bias and consensus. The re...

  17. Forecasts of county-level land uses under three future scenarios: a technical document supporting the Forest Service 2010 RPA Assessment

    Science.gov (United States)

    David N. Wear

    2011-01-01

    Accurately forecasting future forest conditions and the implications for ecosystem services depends on understanding land use dynamics. In support of the 2010 Renewable Resources Planning Act (RPA) Assessment, we forecast changes in land uses for the coterminous United States in response to three scenarios. Our land use models forecast urbanization in response to the...

  18. Uncertainties in Forecasting Streamflow using Entropy Theory

    Science.gov (United States)

    Cui, H.; Singh, V. P.

    2017-12-01

    Streamflow forecasting is essential in river restoration, reservoir operation, power generation, irrigation, navigation, and water management. However, there is always uncertainties accompanied in forecast, which may affect the forecasting results and lead to large variations. Therefore, uncertainties must be considered and be assessed properly when forecasting streamflow for water management. The aim of our work is to quantify the uncertainties involved in forecasting streamflow and provide reliable streamflow forecast. Despite that streamflow time series are stochastic, they exhibit seasonal and periodic patterns. Therefore, streamflow forecasting entails modeling seasonality, periodicity, and its correlation structure, and assessing uncertainties. This study applies entropy theory to forecast streamflow and measure uncertainties during the forecasting process. To apply entropy theory for streamflow forecasting, spectral analysis is combined to time series analysis, as spectral analysis can be employed to characterize patterns of streamflow variation and identify the periodicity of streamflow. That is, it permits to extract significant information for understanding the streamflow process and prediction thereof. Application of entropy theory for streamflow forecasting involves determination of spectral density, determination of parameters, and extension of autocorrelation function. The uncertainties brought by precipitation input, forecasting model and forecasted results are measured separately using entropy. With information theory, how these uncertainties transported and aggregated during these processes will be described.

  19. Evaluating hydrological response to forecasted land-use change—scenario testing with the automated geospatial watershed assessment (AGWA) tool

    Science.gov (United States)

    Kepner, William G.; Semmens, Darius J.; Hernandez, Mariano; Goodrich, David C.

    2009-01-01

    Envisioning and evaluating future scenarios has emerged as a critical component of both science and social decision-making. The ability to assess, report, map, and forecast the life support functions of ecosystems is absolutely critical to our capacity to make informed decisions to maintain the sustainable nature of our ecosystem services now and into the future. During the past two decades, important advances in the integration of remote imagery, computer processing, and spatial-analysis technologies have been used to develop landscape information that can be integrated with hydrologic models to determine long-term change and make predictive inferences about the future. Two diverse case studies in northwest Oregon (Willamette River basin) and southeastern Arizona (San Pedro River) were examined in regard to future land use scenarios relative to their impact on surface water conditions (e.g., sediment yield and surface runoff) using hydrologic models associated with the Automated Geospatial Watershed Assessment (AGWA) tool. The base reference grid for land cover was modified in both study locations to reflect stakeholder preferences 20 to 60 yrs into the future, and the consequences of landscape change were evaluated relative to the selected future scenarios. The two studies provide examples of integrating hydrologic modeling with a scenario analysis framework to evaluate plausible future forecasts and to understand the potential impact of landscape change on ecosystem services.

  20. Assessing uncertainties in flood forecasts for decision making: prototype of an operational flood management system integrating ensemble predictions

    Directory of Open Access Journals (Sweden)

    J. Dietrich

    2009-08-01

    Full Text Available Ensemble forecasts aim at framing the uncertainties of the potential future development of the hydro-meteorological situation. A probabilistic evaluation can be used to communicate forecast uncertainty to decision makers. Here an operational system for ensemble based flood forecasting is presented, which combines forecasts from the European COSMO-LEPS, SRNWP-PEPS and COSMO-DE prediction systems. A multi-model lagged average super-ensemble is generated by recombining members from different runs of these meteorological forecast systems. A subset of the super-ensemble is selected based on a priori model weights, which are obtained from ensemble calibration. Flood forecasts are simulated by the conceptual rainfall-runoff-model ArcEGMO. Parameter uncertainty of the model is represented by a parameter ensemble, which is a priori generated from a comprehensive uncertainty analysis during model calibration. The use of a computationally efficient hydrological model within a flood management system allows us to compute the hydro-meteorological model chain for all members of the sub-ensemble. The model chain is not re-computed before new ensemble forecasts are available, but the probabilistic assessment of the output is updated when new information from deterministic short range forecasts or from assimilation of measured data becomes available. For hydraulic modelling, with the desired result of a probabilistic inundation map with high spatial resolution, a replacement model can help to overcome computational limitations. A prototype of the developed framework has been applied for a case study in the Mulde river basin. However these techniques, in particular the probabilistic assessment and the derivation of decision rules are still in their infancy. Further research is necessary and promising.

  1. Demand forecast model based on CRM

    Science.gov (United States)

    Cai, Yuancui; Chen, Lichao

    2006-11-01

    With interiorizing day by day management thought that regarding customer as the centre, forecasting customer demand becomes more and more important. In the demand forecast of customer relationship management, the traditional forecast methods have very great limitation because much uncertainty of the demand, these all require new modeling to meet the demands of development. In this paper, the notion is that forecasting the demand according to characteristics of the potential customer, then modeling by it. The model first depicts customer adopting uniform multiple indexes. Secondly, the model acquires characteristic customers on the basis of data warehouse and the technology of data mining. The last, there get the most similar characteristic customer by their comparing and forecast the demands of new customer by the most similar characteristic customer.

  2. National Coal Utilization Assessment: a preliminary assessment of coal utilizaton in the South. [Southern USA to 2020; forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Berry, L. B.; Bjornstad, D. J.; Boercker, F. D.

    1978-01-01

    Some of the major problems and issues related to coal development and use in the South are identified and assessed assuming a base-case energy scenario for the next 45 years. This scenario assumes a midrange of coal use and a relatively high rate of nuclear use over the forecast period. The potential impacts from coal development and use are significant, particularly in the 1990-2020 time period. Practically all available sites suitable for power plant development in the assessment will be utilized by 2020. Overall, sulfur dioxide will be well below the annual primary standard; however, several local hot-spot areas were identified. In addition, sulfate concentrations will be increased significantly, particularly over Virginia, West Virginia, and northern Kentucky. Coal mining is expected to affect 6 of the 12 major ecological regions. Coal mining will lead to increased average suspended sediment concentrations in some river basins, and special measures will be required to control acid discharges from active mines in pyritic regions. The increased mining of coal and subsequent sulfur dioxide increases from its combustion may also give rise to a land-use confrontation with food and fiber production. Potential health effects from exposure to sulfur dioxide and sulfates are expected to increase rapidly in several areas, particularly in parts of Kentucky, Maryland, District of Columbia, and Georgia. Regional social costs should be relatively low, although some site-specific costs are expected to be very high. Alternative energy technologies, careful siting selection, and deployment of environmental control technologies and operating policies will be required to reduce or mitigate these potential impacts.

  3. Bayesian flood forecasting methods: A review

    Science.gov (United States)

    Han, Shasha; Coulibaly, Paulin

    2017-08-01

    Over the past few decades, floods have been seen as one of the most common and largely distributed natural disasters in the world. If floods could be accurately forecasted in advance, then their negative impacts could be greatly minimized. It is widely recognized that quantification and reduction of uncertainty associated with the hydrologic forecast is of great importance for flood estimation and rational decision making. Bayesian forecasting system (BFS) offers an ideal theoretic framework for uncertainty quantification that can be developed for probabilistic flood forecasting via any deterministic hydrologic model. It provides suitable theoretical structure, empirically validated models and reasonable analytic-numerical computation method, and can be developed into various Bayesian forecasting approaches. This paper presents a comprehensive review on Bayesian forecasting approaches applied in flood forecasting from 1999 till now. The review starts with an overview of fundamentals of BFS and recent advances in BFS, followed with BFS application in river stage forecasting and real-time flood forecasting, then move to a critical analysis by evaluating advantages and limitations of Bayesian forecasting methods and other predictive uncertainty assessment approaches in flood forecasting, and finally discusses the future research direction in Bayesian flood forecasting. Results show that the Bayesian flood forecasting approach is an effective and advanced way for flood estimation, it considers all sources of uncertainties and produces a predictive distribution of the river stage, river discharge or runoff, thus gives more accurate and reliable flood forecasts. Some emerging Bayesian forecasting methods (e.g. ensemble Bayesian forecasting system, Bayesian multi-model combination) were shown to overcome limitations of single model or fixed model weight and effectively reduce predictive uncertainty. In recent years, various Bayesian flood forecasting approaches have been

  4. Cognitive methodology for forecasting oil and gas industry using pattern-based neural information technologies

    Science.gov (United States)

    Gafurov, O.; Gafurov, D.; Syryamkin, V.

    2018-05-01

    The paper analyses a field of computer science formed at the intersection of such areas of natural science as artificial intelligence, mathematical statistics, and database theory, which is referred to as "Data Mining" (discovery of knowledge in data). The theory of neural networks is applied along with classical methods of mathematical analysis and numerical simulation. The paper describes the technique protected by the patent of the Russian Federation for the invention “A Method for Determining Location of Production Wells during the Development of Hydrocarbon Fields” [1–3] and implemented using the geoinformation system NeuroInformGeo. There are no analogues in domestic and international practice. The paper gives an example of comparing the forecast of the oil reservoir quality made by the geophysicist interpreter using standard methods and the forecast of the oil reservoir quality made using this technology. The technical result achieved shows the increase of efficiency, effectiveness, and ecological compatibility of development of mineral deposits and discovery of a new oil deposit.

  5. An Assessment of Data from the Advanced Technology Microwave Sounder at the Met Office

    Directory of Open Access Journals (Sweden)

    Amy Doherty

    2015-01-01

    Full Text Available An appraisal of the Advanced Technology Microwave Sounder (ATMS for use in numerical weather prediction (NWP is presented, including an assessment of the data quality, the impact on Met Office global forecasts in preoperational trials, and a summary of performance over a period of 17 months operational use. After remapping, the noise performance (NEΔT of the tropospheric temperature sounding channels is evaluated to be approximately 0.1 K, comparing favourably with AMSU-A. However, the noise is not random, differences between observations and simulations based on short-range forecast fields show a spurious striping effect, due to 1/f noise in the receiver. The amplitude of this signal is several tenths of a Kelvin, potentially a concern for NWP applications. In preoperational tests, adding ATMS data to a full Met Office system already exploiting data from four microwave sounders improves southern hemisphere mean sea level pressure forecasts in the 2- to 5-day range by 1-2%. In operational use, where data from five other microwave sounders is assimilated, forecast impact is typically between −0.05 and −0.1 J/kg (3.4% of total mean impact per day over the period 1 April to 31 July 2013. This suggests benefits beyond redundancy, associated with reducing already small analysis errors.

  6. Verification of Space Weather Forecasts using Terrestrial Weather Approaches

    Science.gov (United States)

    Henley, E.; Murray, S.; Pope, E.; Stephenson, D.; Sharpe, M.; Bingham, S.; Jackson, D.

    2015-12-01

    The Met Office Space Weather Operations Centre (MOSWOC) provides a range of 24/7 operational space weather forecasts, alerts, and warnings, which provide valuable information on space weather that can degrade electricity grids, radio communications, and satellite electronics. Forecasts issued include arrival times of coronal mass ejections (CMEs), and probabilistic forecasts for flares, geomagnetic storm indices, and energetic particle fluxes and fluences. These forecasts are produced twice daily using a combination of output from models such as Enlil, near-real-time observations, and forecaster experience. Verification of forecasts is crucial for users, researchers, and forecasters to understand the strengths and limitations of forecasters, and to assess forecaster added value. To this end, the Met Office (in collaboration with Exeter University) has been adapting verification techniques from terrestrial weather, and has been working closely with the International Space Environment Service (ISES) to standardise verification procedures. We will present the results of part of this work, analysing forecast and observed CME arrival times, assessing skill using 2x2 contingency tables. These MOSWOC forecasts can be objectively compared to those produced by the NASA Community Coordinated Modelling Center - a useful benchmark. This approach cannot be taken for the other forecasts, as they are probabilistic and categorical (e.g., geomagnetic storm forecasts give probabilities of exceeding levels from minor to extreme). We will present appropriate verification techniques being developed to address these forecasts, such as rank probability skill score, and comparing forecasts against climatology and persistence benchmarks. As part of this, we will outline the use of discrete time Markov chains to assess and improve the performance of our geomagnetic storm forecasts. We will also discuss work to adapt a terrestrial verification visualisation system to space weather, to help

  7. Projecting technology change to improve space technology planning and systems management

    Science.gov (United States)

    Walk, Steven Robert

    2011-04-01

    Projecting technology performance evolution has been improving over the years. Reliable quantitative forecasting methods have been developed that project the growth, diffusion, and performance of technology in time, including projecting technology substitutions, saturation levels, and performance improvements. These forecasts can be applied at the early stages of space technology planning to better predict available future technology performance, assure the successful selection of technology, and improve technology systems management strategy. Often what is published as a technology forecast is simply scenario planning, usually made by extrapolating current trends into the future, with perhaps some subjective insight added. Typically, the accuracy of such predictions falls rapidly with distance in time. Quantitative technology forecasting (QTF), on the other hand, includes the study of historic data to identify one of or a combination of several recognized universal technology diffusion or substitution patterns. In the same manner that quantitative models of physical phenomena provide excellent predictions of system behavior, so do QTF models provide reliable technological performance trajectories. In practice, a quantitative technology forecast is completed to ascertain with confidence when the projected performance of a technology or system of technologies will occur. Such projections provide reliable time-referenced information when considering cost and performance trade-offs in maintaining, replacing, or migrating a technology, component, or system. This paper introduces various quantitative technology forecasting techniques and illustrates their practical application in space technology and technology systems management.

  8. A patent survey case: how could technological forecasting help cosmetic chemists with product innovation?

    Science.gov (United States)

    Domicio Da Silva Souza, Ivan; Juliana Pinheiro, Bárbara; Passarini Takahashi, Vania

    2012-01-01

    Patents represent a free and open source of data for studying innovation and forecasting technological trends. Thus, we suggest that new discussions about the role of patent information are needed. To illustrate the relevance of this issue, we performed a survey of patents involving skin care products, which were granted by the United States Patent and Trademark Office (USPTO) between 2006 and 2010, to identify opportunities for innovation and technological trends. We quantified the use of technologies in 333 patents. We plotted a life cycle of technologies related to natural ingredients. We also determined the cross impact of the technologies identified. We observed technologies related to processes applied to cosmetics (2.2%), functional packaging and applicators (2.9%), excipients and active compounds (21.5%), and cosmetic preparations (73.5%). Further, 21.6% of the patents were related to the use of natural ingredients. Several opportunities for innovation were discussed throughout this paper, for example, the use of peptides as active compounds or intracellular carriers (only 3.9% of the technologies in cosmetic preparations). We also observed technological cross impacts that suggested a trend toward multifunctional cosmetics, among others. Patent surveys may help researchers with product innovation because they allow us to identify available and unexplored technologies and turn them into whole new concepts.

  9. Succeeding in deep water by combining technology qualification and production forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Hussain, A.; Oiungen, B.; Raposo, C. [Det Norske Veritas (DNV), Rio de Janeiro, RJ (Brazil)

    2008-07-01

    All the easy oil and gas is gone, and, as a result the Oil and Gas industry is continuously targeting deeper and more remote fields. The exploration and development of deep water oil and gas fields is associated with enormous costs and multiple uncertainties with regard to equipment reliability and performance. Proper risk management can be used to evaluate the impact of these uncertainties thereby helping to ensure optimal business performance of the future assets, as well as helping the decision maker target investment towards areas where the financial impact will be the greatest. This paper reviews the principles of Technology Qualification and Production Forecasting methodology, both of which are risk management solutions with a proven track record for deep water field developments. (author)

  10. Assessment of a new seasonal to inter-annual operational Great Lakes water supply, water levels, and connecting channel flow forecasting system

    Science.gov (United States)

    Gronewold, A.; Fry, L. M.; Hunter, T.; Pei, L.; Smith, J.; Lucier, H.; Mueller, R.

    2017-12-01

    The U.S. Army Corps of Engineers (USACE) has recently operationalized a suite of ensemble forecasts of Net Basin Supply (NBS), water levels, and connecting channel flows that was developed through a collaboration among USACE, NOAA's Great Lakes Environmental Research Laboratory, Ontario Power Generation (OPG), New York Power Authority (NYPA), and the Niagara River Control Center (NRCC). These forecasts are meant to provide reliable projections of potential extremes in daily discharge in the Niagara and St. Lawrence Rivers over a long time horizon (5 years). The suite of forecasts includes eight configurations that vary by (a) NBS model configuration, (b) meteorological forcings, and (c) incorporation of seasonal climate projections through the use of weighting. Forecasts are updated on a weekly basis, and represent the first operational forecasts of Great Lakes water levels and flows that span daily to inter-annual horizons and employ realistic regulation logic and lake-to-lake routing. We will present results from a hindcast assessment conducted during the transition from research to operation, as well as early indications of success rates determined through operational verification of forecasts. Assessment will include an exploration of the relative skill of various forecast configurations at different time horizons and the potential for application to hydropower decision making and Great Lakes water management.

  11. Technology Alignment and Portfolio Prioritization (TAPP): Advanced Methods in Strategic Analysis, Technology Forecasting and Long Term Planning for Human Exploration and Operations, Advanced Exploration Systems and Advanced Concepts

    Science.gov (United States)

    Funaro, Gregory V.; Alexander, Reginald A.

    2015-01-01

    Prioritization by Similarity to Ideal Solution (TOPSIS), and other multi­-criteria decision-making methods. These methods can be labor-intensive, often contain cognitive or parochial bias, and do not consider the competing prioritization between mission architectures. Strategic Decision-Making (SDM) processes cannot be properly understood unless the context of the technology is understood. This makes assessing technological change particularly challenging due to the relationships "between incumbent technology and the incumbent (innovation) system in relation to the emerging technology and the emerging innovation system." The central idea in technology dynamics is to consider all activities that contribute to the development, diffusion, and use of innovations as system functions. Bergek defines system functions within a TIS to address what is actually happening and has a direct influence on the ultimate performance of the system and technology development. ACO uses similar metrics and is expanding these metrics to account for the structure and context of the technology. At NASA technology and strategy is strongly interrelated. NASA's Strategic Space Technology Investment Plan (SSTIP) prioritizes those technologies essential to the pursuit of NASA's missions and national interests. The SSTIP is strongly coupled with NASA's Technology Roadmaps to provide investment guidance during the next four years, within a twenty-year horizon. This paper discusses the methods ACO is currently developing to better perform technology assessments while taking into consideration Strategic Alignment, Technology Forecasting, and Long Term Planning.

  12. Technological forecasting a long time of the scientific-technological development of the nuclear fusion

    International Nuclear Information System (INIS)

    Schettert, Plinio G.; Oliveira, Wagner S.; Aquino, Afonso R.

    2009-01-01

    With base in the introduction in long time of the nuclear fusion inside of a system of viable energy, taking in consideration economic factors, would imply on investment in a long period. The objective of this project utilizing the method of the Delphi technique is the technological forecast a long time of the scientific-technological development of the nuclear fusion and its impact. This research project will be carried through different stages of improvement of variables. A questionnaire based on information and analysis of the literature validated for specialists in nuclear fusion becomes this project a tool in the elaboration future of a database contends variables on the theme nuclear fusion and its perspectives. The database will be composed for the answers and suggestions obtained, with exploratory and extrapolatory elements, on the theme a great number of specialists involving in the nuclear fusion area. The database is analyzed for the configuration of variables that represent elements as scientific-technological factors, economical, political, social and environmental among others. As final result of the research with the Delphi technique, different scenes obtained with the variables will be indicated by convergent factors or not on the approached perspectives. The analysis of the data will be possible through of improve of statistical analysis tools. This is the first analyzes of the answers. The questionnaire was validated with nuclear fusion specialists from the Institute of Physics of the University of Sao Paulo in Brazil and the Center of Nuclear Fusion of the Technical University of Lisbon in Portugal. (author)

  13. An Assessment of the Skill of GEOS-5 Seasonal Forecasts

    Science.gov (United States)

    Ham, Yoo-Geun; Schubert, Siegfried D.; Rienecker, Michele M.

    2013-01-01

    The seasonal forecast skill of the NASA Global Modeling and Assimilation Office coupled global climate model (CGCM) is evaluated based on an ensemble of 9-month lead forecasts for the period 1993 to 2010. The results from the current version (V2) of the CGCM consisting of the GEOS-5 AGM coupled to the MOM4 ocean model are compared with those from an earlier version (V1) in which the AGCM (the NSIPP model) was coupled to the Poseidon Ocean Model. It was found that the correlation skill of the Sea Surface Temperature (SST) forecasts is generally better in V2, especially over the sub-tropical and tropical central and eastern Pacific, Atlantic, and Indian Ocean. Furthermore, the improvement in skill in V2 mainly comes from better forecasts of the developing phase of ENSO from boreal spring to summer. The skill of ENSO forecasts initiated during the boreal winter season, however, shows no improvement in terms of correlation skill, and is in fact slightly worse in terms of root mean square error (RMSE). The degradation of skill is found to be due to an excessive ENSO amplitude. For V1, the ENSO amplitude is too strong in forecasts starting in boreal spring and summer, which causes large RMSE in the forecast. For V2, the ENSO amplitude is slightly stronger than that in observations and V1 for forecasts starting in boreal winter season. An analysis of the terms in the SST tendency equation, shows that this is mainly due to an excessive zonal advective feedback. In addition, V2 forecasts that are initiated during boreal winter season, exhibit a slower phase transition of El Nino, which is consistent with larger amplitude of ENSO after the ENSO peak season. It is found that this is due to weak discharge of equatorial Warm Water Volume (WWV). In both observations and V1, the discharge of equatorial WWV leads the equatorial geostrophic easterly current so as to damp the El Nino starting in January. This process is delayed by about 2 months in V2 due to the slower phase

  14. Statistical and RBF NN models : providing forecasts and risk assessment

    OpenAIRE

    Marček, Milan

    2009-01-01

    Forecast accuracy of economic and financial processes is a popular measure for quantifying the risk in decision making. In this paper, we develop forecasting models based on statistical (stochastic) methods, sometimes called hard computing, and on a soft method using granular computing. We consider the accuracy of forecasting models as a measure for risk evaluation. It is found that the risk estimation process based on soft methods is simplified and less critical to the question w...

  15. Forecasting droughts in West Africa: Operational practice and refined seasonal precipitation forecasts

    Science.gov (United States)

    Bliefernicht, Jan; Siegmund, Jonatan; Seidel, Jochen; Arnold, Hanna; Waongo, Moussa; Laux, Patrick; Kunstmann, Harald

    2016-04-01

    Precipitation forecasts for the upcoming rainy seasons are one of the most important sources of information for an early warning of droughts and water scarcity in West Africa. The meteorological services in West Africa perform seasonal precipitation forecasts within the framework of PRESAO (the West African climate outlook forum) since the end of the 1990s. Various sources of information and statistical techniques are used by the individual services to provide a harmonized seasonal precipitation forecasts for decision makers in West Africa. In this study, we present a detailed overview of the operational practice in West Africa including a first statistical assessment of the performance of the precipitation forecasts for drought situations for the past 18 years (1998 to 2015). In addition, a long-term hindcasts (1982 to 2009) and a semi-operational experiment for the rainy season 2013 using statistical and/or dynamical downscaling are performed to refine the precipitation forecasts from the Climate Forecast System Version 2 (CFSv2), a global ensemble prediction system. This information is post-processed to provide user-oriented precipitation indices such as the onset of the rainy season for supporting water and land use management for rain-fed agriculture. The evaluation of the individual techniques is performed focusing on water-scarce regions of the Volta basin in Burkina Faso and Ghana. The forecasts of the individual techniques are compared to state-of-the-art global observed precipitation products and a novel precipitation database based on long-term daily rain-gage measurements provided by the national meteorological services. The statistical assessment of the PRESAO forecasts indicates skillful seasonal precipitation forecasts for many locations in the Volta basin, particularly for years with water deficits. The operational experiment for the rainy season 2013 illustrates the high potential of a physically-based downscaling for this region but still shows

  16. Forecasting metal prices: Do forecasters herd?

    DEFF Research Database (Denmark)

    Pierdzioch, C.; Rulke, J. C.; Stadtmann, G.

    2013-01-01

    We analyze more than 20,000 forecasts of nine metal prices at four different forecast horizons. We document that forecasts are heterogeneous and report that anti-herding appears to be a source of this heterogeneity. Forecaster anti-herding reflects strategic interactions among forecasters...

  17. Assessing the value of increased model resolution in forecasting fire danger

    Science.gov (United States)

    Jeanne Hoadley; Miriam Rorig; Ken Westrick; Larry Bradshaw; Sue Ferguson; Scott Goodrick; Paul Werth

    2003-01-01

    The fire season of 2000 was used as a case study to assess the value of increasing mesoscale model resolution for fire weather and fire danger forecasting. With a domain centered on Western Montana and Northern Idaho, MM5 simulations were run at 36, 12, and 4-km resolutions for a 30 day period at the height of the fire season. Verification analyses for meteorological...

  18. Ensemble Forecasts with Useful Skill-Spread Relationships for African meningitis and Asia Streamflow Forecasting

    Science.gov (United States)

    Hopson, T. M.

    2014-12-01

    One potential benefit of an ensemble prediction system (EPS) is its capacity to forecast its own forecast error through the ensemble spread-error relationship. In practice, an EPS is often quite limited in its ability to represent the variable expectation of forecast error through the variable dispersion of the ensemble, and perhaps more fundamentally, in its ability to provide enough variability in the ensembles dispersion to make the skill-spread relationship even potentially useful (irrespective of whether the EPS is well-calibrated or not). In this paper we examine the ensemble skill-spread relationship of an ensemble constructed from the TIGGE (THORPEX Interactive Grand Global Ensemble) dataset of global forecasts and a combination of multi-model and post-processing approaches. Both of the multi-model and post-processing techniques are based on quantile regression (QR) under a step-wise forward selection framework leading to ensemble forecasts with both good reliability and sharpness. The methodology utilizes the ensemble's ability to self-diagnose forecast instability to produce calibrated forecasts with informative skill-spread relationships. A context for these concepts is provided by assessing the constructed ensemble in forecasting district-level humidity impacting the incidence of meningitis in the meningitis belt of Africa, and in forecasting flooding events in the Brahmaputra and Ganges basins of South Asia.

  19. Electrical Load Survey and Forecast for a Decentralized Hybrid ...

    African Journals Online (AJOL)

    Electrical Load Survey and Forecast for a Decentralized Hybrid Power System at Elebu, Kwara State, Nigeria. ... Nigerian Journal of Technology ... The paper reports the results of electrical load demand and forecast for Elebu rural community ...

  20. Long-term forecast 2010; Laangsiktsprognos 2010

    Energy Technology Data Exchange (ETDEWEB)

    2011-07-01

    This report presents the energy forecast to the year 2030, and two different sensitivity scenarios. The forecast is based on existing instruments, which means that the report's findings should not be considered a proper forecast of the future energy use, but as an impact assessment of existing policy instruments, given different circumstances such as economic growth and fuel prices

  1. LHCb Computing Resources: 2012 re-assessment, 2013 request and 2014 forecast

    CERN Document Server

    Graciani Diaz, Ricardo

    2012-01-01

    This note covers the following aspects: re-assessment of computing resource usage estimates for 2012 data-taking period, request of computing resource needs for 2013, and a first forecast of the 2014 needs, when restart of data-taking is foreseen. Estimates are based on 2011 experience, as well as on the results of a simulation of the computing model described in the document. Differences in the model and deviations in the estimates from previous presented results are stressed.

  2. Forecasting Costa Rican Quarterly Growth with Mixed-frequency Models

    Directory of Open Access Journals (Sweden)

    Adolfo Rodríguez Vargas

    2014-11-01

    Full Text Available We assess the utility of mixed-frequency models to forecast the quarterly growth rate of Costa Rican real GDP: we estimate bridge and MiDaS models with several lag lengths using information of the IMAE and compute forecasts (horizons of 0-4 quarters which are compared between themselves, with those of ARIMA models and with those resulting from forecast combinations. Combining the most accurate forecasts is most useful when forecasting in real time, whereas MiDaS forecasts are the best-performing overall: as the forecasting horizon increases, their precisionis affected relatively little; their success rates in predicting the direction of changes in the growth rate are stable, and several forecastsremain unbiased. In particular, forecasts computed from simple MiDaS with 9 and 12 lags are unbiased at all horizons and information sets assessed, and show the highest number of significant differences in forecasting ability in comparison with all other models.

  3. Combining Reference Class Forecasting with Overconfidence Theory for Better Risk Assessment of Transport Infrastructure Investments

    DEFF Research Database (Denmark)

    Leleur, Steen; Salling, Kim Bang; Pilkauskiene, Inga

    2015-01-01

    investments. In the last decade progress has been made by dealing with this situation known as planners’ optimism bias. Especially attention can be drawn to the use of reference class forecasting that has led to adjustment factors that, when used on the estimates of costs and demand, lead to cost......-benefit analysis results that are modified by taking historical risk experience into account. This article seeks to add to this progress in risk assessment methodology in two ways: first it suggests to apply reference class forecasting (RCF) in a flexible way where the effort is focused on formulating the best...

  4. The case for better PV forecasting

    DEFF Research Database (Denmark)

    Alet, Pierre-Jean; Efthymiou, Venizelos; Graditi, Giorgio

    2016-01-01

    Rising levels of PV penetration mean increasingly sophisticated forecasting technologies are needed to maintain grid stability and maximise the economic value of PV systems. The Grid Integration working group of the European Technology and Innovation Platform – Photovoltaics (ETIP PV) shares the ...

  5. On Long Memory Origins and Forecast Horizons

    DEFF Research Database (Denmark)

    Vera-Valdés, J. Eduardo

    Most long memory forecasting studies assume that the memory is generated by the fractional difference operator. We argue that the most cited theoretical arguments for the presence of long memory do not imply the fractional difference operator, and assess the performance of the autoregressive...... fractionally integrated moving average (ARFIMA) model when forecasting series with long memory generated by nonfractional processes. We find that high-order autoregressive (AR) models produce similar or superior forecast performance than ARFIMA models at short horizons. Nonetheless, as the forecast horizon...... increases, the ARFIMA models tend to dominate in forecast performance. Hence, ARFIMA models are well suited for forecasts of long memory processes regardless of the long memory generating mechanism, particularly for medium and long forecast horizons. Additionally, we analyse the forecasting performance...

  6. Real-time forecasts of flood hazard and impact: some UK experiences

    Directory of Open Access Journals (Sweden)

    Cole Steven J.

    2016-01-01

    Full Text Available Major UK floods over the last decade have motivated significant technological and scientific advances in operational flood forecasting and warning. New joint forecasting centres between the national hydrological and meteorological operating agencies have been formed that issue a daily, national Flood Guidance Statement (FGS to the emergency response community. The FGS is based on a Flood Risk Matrix approach that is a function of potential impact severity and likelihood. It has driven an increased demand for robust, accurate and timely forecast and alert information on fluvial and surface water flooding along with impact assessments. The Grid-to-Grid (G2G distributed hydrological model has been employed across Britain at a 1km resolution to support the FGS. Novel methods for linking dynamic gridded estimates of river flow and surface runoff with more detailed offline flood risk maps have been developed to obtain real-time probabilistic forecasts of potential impacts, leading to operational trials. Examples of the national-scale G2G application are provided along with case studies of forecast flood impact from (i an operational Surface Water Flooding (SWF trial during the Glasgow 2014 Commonwealth Games, (ii SWF developments under the Natural Hazards Partnership over England & Wales, and (iii fluvial applications in Scotland.

  7. National forecast for geothermal resource exploration and development with techniques for policy analysis and resource assessment

    Energy Technology Data Exchange (ETDEWEB)

    Cassel, T.A.V.; Shimamoto, G.T.; Amundsen, C.B.; Blair, P.D.; Finan, W.F.; Smith, M.R.; Edeistein, R.H.

    1982-03-31

    The backgrund, structure and use of modern forecasting methods for estimating the future development of geothermal energy in the United States are documented. The forecasting instrument may be divided into two sequential submodels. The first predicts the timing and quality of future geothermal resource discoveries from an underlying resource base. This resource base represents an expansion of the widely-publicized USGS Circular 790. The second submodel forecasts the rate and extent of utilization of geothermal resource discoveries. It is based on the joint investment behavior of resource developers and potential users as statistically determined from extensive industry interviews. It is concluded that geothermal resource development, especially for electric power development, will play an increasingly significant role in meeting US energy demands over the next 2 decades. Depending on the extent of R and D achievements in related areas of geosciences and technology, expected geothermal power development will reach between 7700 and 17300 Mwe by the year 2000. This represents between 8 and 18% of the expected electric energy demand (GWh) in western and northwestern states.

  8. Integrating observation and statistical forecasts over sub-Saharan Africa to support Famine Early Warning

    Science.gov (United States)

    Funk, Chris; Verdin, James P.; Husak, Gregory

    2007-01-01

    Famine early warning in Africa presents unique challenges and rewards. Hydrologic extremes must be tracked and anticipated over complex and changing climate regimes. The successful anticipation and interpretation of hydrologic shocks can initiate effective government response, saving lives and softening the impacts of droughts and floods. While both monitoring and forecast technologies continue to advance, discontinuities between monitoring and forecast systems inhibit effective decision making. Monitoring systems typically rely on high resolution satellite remote-sensed normalized difference vegetation index (NDVI) and rainfall imagery. Forecast systems provide information on a variety of scales and formats. Non-meteorologists are often unable or unwilling to connect the dots between these disparate sources of information. To mitigate these problem researchers at UCSB's Climate Hazard Group, NASA GIMMS and USGS/EROS are implementing a NASA-funded integrated decision support system that combines the monitoring of precipitation and NDVI with statistical one-to-three month forecasts. We present the monitoring/forecast system, assess its accuracy, and demonstrate its application in food insecure sub-Saharan Africa.

  9. Value of Forecaster in the Loop

    Science.gov (United States)

    2014-09-01

    forecast system IFR instrument flight rules IMC instrument meteorological conditions LAMP Localized Aviation Model Output Statistics Program METOC...obtaining valuable experience. Additional factors have impacted the Navy weather forecast process. There has been a the realignment of the meteorology...forecasts that are assessed, it may be a relatively small number that have direct impact on the decision-making process. Whether the value is minimal or

  10. Mid-term load forecasting of power systems by a new prediction method

    International Nuclear Information System (INIS)

    Amjady, Nima; Keynia, Farshid

    2008-01-01

    Mid-term load forecasting (MTLF) becomes an essential tool for today power systems, mainly in those countries whose power systems operate in a deregulated environment. Among different kinds of MTLF, this paper focuses on the prediction of daily peak load for one month ahead. This kind of load forecast has many applications like maintenance scheduling, mid-term hydro thermal coordination, adequacy assessment, management of limited energy units, negotiation of forward contracts, and development of cost efficient fuel purchasing strategies. However, daily peak load is a nonlinear, volatile, and nonstationary signal. Besides, lack of sufficient data usually further complicates this problem. The paper proposes a new methodology to solve it, composed of an efficient data model, preforecast mechanism and combination of neural network and evolutionary algorithm as the hybrid forecast technique. The proposed methodology is examined on the EUropean Network on Intelligent TEchnologies (EUNITE) test data and Iran's power system. We will also compare our strategy with the other MTLF methods revealing its capability to solve this load forecast problem

  11. LHCb Computing Resources: 2011 re-assessment, 2012 request and 2013 forecast

    CERN Document Server

    Graciani, R

    2011-01-01

    This note covers the following aspects: re-assessment of computing resource usage estimates for 2011 data taking period, request of computing resource needs for 2012 data taking period and a first forecast of the 2013 needs, when no data taking is foreseen. Estimates are based on 2010 experienced and last updates from LHC schedule, as well as on a new implementation of the computing model simulation tool. Differences in the model and deviations in the estimates from previous presented results are stressed.

  12. Assessment of the potential forecasting skill of a global hydrological model in reproducing the occurrence of monthly flow extremes

    Directory of Open Access Journals (Sweden)

    N. Candogan Yossef

    2012-11-01

    Full Text Available As an initial step in assessing the prospect of using global hydrological models (GHMs for hydrological forecasting, this study investigates the skill of the GHM PCR-GLOBWB in reproducing the occurrence of past extremes in monthly discharge on a global scale. Global terrestrial hydrology from 1958 until 2001 is simulated by forcing PCR-GLOBWB with daily meteorological data obtained by downscaling the CRU dataset to daily fields using the ERA-40 reanalysis. Simulated discharge values are compared with observed monthly streamflow records for a selection of 20 large river basins that represent all continents and a wide range of climatic zones.

    We assess model skill in three ways all of which contribute different information on the potential forecasting skill of a GHM. First, the general skill of the model in reproducing hydrographs is evaluated. Second, model skill in reproducing significantly higher and lower flows than the monthly normals is assessed in terms of skill scores used for forecasts of categorical events. Third, model skill in reproducing flood and drought events is assessed by constructing binary contingency tables for floods and droughts for each basin. The skill is then compared to that of a simple estimation of discharge from the water balance (PE.

    The results show that the model has skill in all three types of assessments. After bias correction the model skill in simulating hydrographs is improved considerably. For most basins it is higher than that of the climatology. The skill is highest in reproducing monthly anomalies. The model also has skill in reproducing floods and droughts, with a markedly higher skill in floods. The model skill far exceeds that of the water balance estimate. We conclude that the prospect for using PCR-GLOBWB for monthly and seasonal forecasting of the occurrence of hydrological extremes is positive. We argue that this conclusion applies equally to other similar GHMs and

  13. On forecasting ionospheric total electron content responses to high-speed solar wind streams

    Directory of Open Access Journals (Sweden)

    Meng Xing

    2016-01-01

    Full Text Available Conditions in the ionosphere have become increasingly important to forecast, since more and more spaceborne and ground-based technological systems rely on ionospheric weather. Here we explore the feasibility of ionospheric forecasts with the current generation of physics-based models. In particular, we focus on total electron content (TEC predictions using the Global Ionosphere-Thermosphere Model (GITM. Simulations are configured in a forecast mode and performed for four typical high-speed-stream events during 2007–2012. The simulated TECs are quantified through a metric, which divides the globe into a number of local regions and robustly differentiates between quiet and disturbed periods. Proposed forecast products are hourly global maps color-coded by the TEC disturbance level of each local region. To assess the forecasts, we compare the simulated TEC disturbances with global TEC maps derived from Global Positioning System (GPS satellite observations. The forecast performance is found to be merely acceptable, with a large number of regions where the observed variations are not captured by the simulations. Examples of model-data agreements and disagreements are investigated in detail, aiming to understand the model behavior and improve future forecasts. For one event, we identify two adjacent regions with similar TEC observations but significant differences in how local chemistry versus plasma transport contribute to electron density changes in the simulation. Suggestions for further analysis are described.

  14. Statistical Models to Assess the Health Effects and to Forecast Ground Level Ozone

    Czech Academy of Sciences Publication Activity Database

    Schlink, U.; Herbath, O.; Richter, M.; Dorling, S.; Nunnari, G.; Cawley, G.; Pelikán, Emil

    2006-01-01

    Roč. 21, č. 4 (2006), s. 547-558 ISSN 1364-8152 R&D Projects: GA AV ČR 1ET400300414 Institutional research plan: CEZ:AV0Z10300504 Keywords : statistical models * ground level ozone * health effects * logistic model * forecasting * prediction performance * neural network * generalised additive model * integrated assessment Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.992, year: 2006

  15. Assessing medical technologies in development; a new paradigm of medical technology assessment

    NARCIS (Netherlands)

    Hummel, J. Marjan; van Rossum, Wouter; Verkerke, Gijsbertus Jacob; Rakhorst, Gerhard

    2000-01-01

    Objective: Our study aims to provide a practical contribution to the field of medical technology assessment within a new paradigm. This paradigm indicates the need for more comprehensive technology assessments in the development stage of a new technology. - Method: We introduce a method, based on

  16. Assessing medical technologies in development - A new paradigm of medical technology assessment

    NARCIS (Netherlands)

    Hummel, MJM; van Rossum, W; Verkerke, GJ; Rakhorst, G

    2000-01-01

    Objective: Our study aims to provide a practical contribution to the field of medical technology assessment within a new paradigm. This paradigm indicates the need for more comprehensive technology assessments in the development stage of a new technology. Method: We introduce a method, based on

  17. EU pharmaceutical expenditure forecast

    OpenAIRE

    Urbinati, Duccio; Rémuzat, Cécile; Kornfeld, Åsa; Vataire, Anne-Lise; Cetinsoy, Laurent; Aballéa, Samuel; Mzoughi, Olfa; Toumi, Mondher

    2014-01-01

    Background and Objectives: With constant incentives for healthcare payers to contain their pharmaceutical budgets, forecasting has become critically important. Some countries have, for instance, developed pharmaceutical horizon scanning units. The objective of this project was to build a model to assess the net effect of the entrance of new patented medicinal products versus medicinal products going off-patent, with a defined forecast horizon, on selected European Union (EU) Member States’ ph...

  18. GMDH-Based Semi-Supervised Feature Selection for Electricity Load Classification Forecasting

    Directory of Open Access Journals (Sweden)

    Lintao Yang

    2018-01-01

    Full Text Available With the development of smart power grids, communication network technology and sensor technology, there has been an exponential growth in complex electricity load data. Irregular electricity load fluctuations caused by the weather and holiday factors disrupt the daily operation of the power companies. To deal with these challenges, this paper investigates a day-ahead electricity peak load interval forecasting problem. It transforms the conventional continuous forecasting problem into a novel interval forecasting problem, and then further converts the interval forecasting problem into the classification forecasting problem. In addition, an indicator system influencing the electricity load is established from three dimensions, namely the load series, calendar data, and weather data. A semi-supervised feature selection algorithm is proposed to address an electricity load classification forecasting issue based on the group method of data handling (GMDH technology. The proposed algorithm consists of three main stages: (1 training the basic classifier; (2 selectively marking the most suitable samples from the unclassified label data, and adding them to an initial training set; and (3 training the classification models on the final training set and classifying the test samples. An empirical analysis of electricity load dataset from four Chinese cities is conducted. Results show that the proposed model can address the electricity load classification forecasting problem more efficiently and effectively than the FW-Semi FS (forward semi-supervised feature selection and GMDH-U (GMDH-based semi-supervised feature selection for customer classification models.

  19. An application and verification of ensemble forecasting on wind power to assess operational risk indicators in power grids

    Energy Technology Data Exchange (ETDEWEB)

    Alessandrini, S.; Ciapessoni, E.; Cirio, D.; Pitto, A.; Sperati, S. [Ricerca sul Sistema Energetico RSE S.p.A., Milan (Italy). Power System Development Dept. and Environment and Sustainable Development Dept.; Pinson, P. [Technical University of Denmark, Lyngby (Denmark). DTU Informatics

    2012-07-01

    Wind energy is part of the so-called not schedulable renewable sources, i.e. it must be exploited when it is available, otherwise it is lost. In European regulation it has priority of dispatch over conventional generation, to maximize green energy production. However, being variable and uncertain, wind (and solar) generation raises several issues for the security of the power grids operation. In particular, Transmission System Operators (TSOs) need as accurate as possible forecasts. Nowadays a deterministic approach in wind power forecasting (WPF) could easily be considered insufficient to face the uncertainty associated to wind energy. In order to obtain information about the accuracy of a forecast and a reliable estimation of its uncertainty, probabilistic forecasting is becoming increasingly widespread. In this paper we investigate the performances of the COnsortium for Small-scale MOdelling Limited area Ensemble Prediction System (COSMO-LEPS). First the ensemble application is followed by assessment of its properties (i.e. consistency, reliability) using different verification indices and diagrams calculated on wind power. Then we provide examples of how EPS based wind power forecast can be used in power system security analyses. Quantifying the forecast uncertainty allows to determine more accurately the regulation reserve requirements, hence improving security of operation and reducing system costs. In particular, the paper also presents a probabilistic power flow (PPF) technique developed at RSE and aimed to evaluate the impact of wind power forecast accuracy on the probability of security violations in power systems. (orig.)

  20. How will climate novelty influence ecological forecasts? Using the Quaternary to assess future reliability.

    Science.gov (United States)

    Fitzpatrick, Matthew C; Blois, Jessica L; Williams, John W; Nieto-Lugilde, Diego; Maguire, Kaitlin C; Lorenz, David J

    2018-03-23

    Future climates are projected to be highly novel relative to recent climates. Climate novelty challenges models that correlate ecological patterns to climate variables and then use these relationships to forecast ecological responses to future climate change. Here, we quantify the magnitude and ecological significance of future climate novelty by comparing it to novel climates over the past 21,000 years in North America. We then use relationships between model performance and climate novelty derived from the fossil pollen record from eastern North America to estimate the expected decrease in predictive skill of ecological forecasting models as future climate novelty increases. We show that, in the high emissions scenario (RCP 8.5) and by late 21st century, future climate novelty is similar to or higher than peak levels of climate novelty over the last 21,000 years. The accuracy of ecological forecasting models is projected to decline steadily over the coming decades in response to increasing climate novelty, although models that incorporate co-occurrences among species may retain somewhat higher predictive skill. In addition to quantifying future climate novelty in the context of late Quaternary climate change, this work underscores the challenges of making reliable forecasts to an increasingly novel future, while highlighting the need to assess potential avenues for improvement, such as increased reliance on geological analogs for future novel climates and improving existing models by pooling data through time and incorporating assemblage-level information. © 2018 John Wiley & Sons Ltd.

  1. Satellites, tweets, forecasts: the future of flood disaster management?

    Science.gov (United States)

    Dottori, Francesco; Kalas, Milan; Lorini, Valerio; Wania, Annett; Pappenberger, Florian; Salamon, Peter; Ramos, Maria Helena; Cloke, Hannah; Castillo, Carlos

    2017-04-01

    Floods have devastating effects on lives and livelihoods around the world. Structural flood defence measures such as dikes and dams can help protect people. However, it is the emerging science and technologies for flood disaster management and preparedness, such as increasingly accurate flood forecasting systems, high-resolution satellite monitoring, rapid risk mapping, and the unique strength of social media information and crowdsourcing, that are most promising for reducing the impacts of flooding. Here, we describe an innovative framework which integrates in real-time two components of the Copernicus Emergency mapping services, namely the European Flood Awareness System and the satellite-based Rapid Mapping, with new procedures for rapid risk assessment and social media and news monitoring. The integrated framework enables improved flood impact forecast, thanks to the real-time integration of forecasting and monitoring components, and increases the timeliness and efficiency of satellite mapping, with the aim of capturing flood peaks and following the evolution of flooding processes. Thanks to the proposed framework, emergency responders will have access to a broad range of timely and accurate information for more effective and robust planning, decision-making, and resource allocation.

  2. Assessing methods for developing crop forecasting in the Iberian Peninsula

    Science.gov (United States)

    Ines, A. V. M.; Capa Morocho, M. I.; Baethgen, W.; Rodriguez-Fonseca, B.; Han, E.; Ruiz Ramos, M.

    2015-12-01

    Seasonal climate prediction may allow predicting crop yield to reduce the vulnerability of agricultural production to climate variability and its extremes. It has been already demonstrated that seasonal climate predictions at European (or Iberian) scale from ensembles of global coupled climate models have some skill (Palmer et al., 2004). The limited predictability that exhibits the atmosphere in mid-latitudes, and therefore de Iberian Peninsula (PI), can be managed by a probabilistic approach based in terciles. This study presents an application for the IP of two methods for linking tercile-based seasonal climate forecasts with crop models to improve crop predictability. Two methods were evaluated and applied for disaggregating seasonal rainfall forecasts into daily weather realizations: 1) a stochastic weather generator and 2) a forecast tercile resampler. Both methods were evaluated in a case study where the impacts of two seasonal rainfall forecasts (wet and dry forecast for 1998 and 2015 respectively) on rainfed wheat yield and irrigation requirements of maize in IP were analyzed. Simulated wheat yield and irrigation requirements of maize were computed with the crop models CERES-wheat and CERES-maize which are included in Decision Support System for Agrotechnology Transfer (DSSAT v.4.5, Hoogenboom et al., 2010). Simulations were run at several locations in Spain where the crop model was calibrated and validated with independent field data. These methodologies would allow quantifying the benefits and risks of a seasonal climate forecast to potential users as farmers, agroindustry and insurance companies in the IP. Therefore, we would be able to establish early warning systems and to design crop management adaptation strategies that take advantage of favorable conditions or reduce the effect of adverse ones. ReferencesPalmer, T. et al., 2004. Development of a European multimodel ensemble system for seasonal-to-interannual prediction (DEMETER). Bulletin of the

  3. Six rules for accurate effective forecasting.

    Science.gov (United States)

    Saffo, Paul

    2007-01-01

    The primary goal of forecasting is to identify the full range of possibilities facing a company, society, or the world at large. In this article, Saffo demythologizes the forecasting process to help executives become sophisticated and participative consumers of forecasts, rather than passive absorbers. He illustrates how to use forecasts to at once broaden understanding of possibilities and narrow the decision space within which one must exercise intuition. The events of 9/11, for example, were a much bigger surprise than they should have been. After all, airliners flown into monuments were the stuff of Tom Clancy novels in the 1990s, and everyone knew that terrorists had a very personal antipathy toward the World Trade Center. So why was 9/11 such a surprise? What can executives do to avoid being blind-sided by other such wild cards, be they radical shifts in markets or the seemingly sudden emergence of disruptive technologies? In describing what forecasters are trying to achieve, Saffo outlines six simple, commonsense rules that smart managers should observe as they embark on a voyage of discovery with professional forecasters. Map a cone of uncertainty, he advises, look for the S curve, embrace the things that don't fit, hold strong opinions weakly, look back twice as far as you look forward, and know when not to make a forecast.

  4. Data Assimilation and Air Quality Forecasting

    NARCIS (Netherlands)

    Eskes, H.; Timmermans, R.; Curier, L.; Ruyter de Wildt, M. de; Segers, A.; Sauter, F.; Schaap, M.

    2014-01-01

    Lotos-Euros is a chemistry transportmodel developed in the Netherlands, and is used for air quality assessments and forecasts. Operational air quality forecasts for the Netherlands concerning ozone and PM10 are made available on the RIVM webpage (http://www.lml.rivm.nl/verw.html) and are used to

  5. Statistical Basis for Predicting Technological Progress

    Science.gov (United States)

    Nagy, Béla; Farmer, J. Doyne; Bui, Quan M.; Trancik, Jessika E.

    2013-01-01

    Forecasting technological progress is of great interest to engineers, policy makers, and private investors. Several models have been proposed for predicting technological improvement, but how well do these models perform? An early hypothesis made by Theodore Wright in 1936 is that cost decreases as a power law of cumulative production. An alternative hypothesis is Moore's law, which can be generalized to say that technologies improve exponentially with time. Other alternatives were proposed by Goddard, Sinclair et al., and Nordhaus. These hypotheses have not previously been rigorously tested. Using a new database on the cost and production of 62 different technologies, which is the most expansive of its kind, we test the ability of six different postulated laws to predict future costs. Our approach involves hindcasting and developing a statistical model to rank the performance of the postulated laws. Wright's law produces the best forecasts, but Moore's law is not far behind. We discover a previously unobserved regularity that production tends to increase exponentially. A combination of an exponential decrease in cost and an exponential increase in production would make Moore's law and Wright's law indistinguishable, as originally pointed out by Sahal. We show for the first time that these regularities are observed in data to such a degree that the performance of these two laws is nearly the same. Our results show that technological progress is forecastable, with the square root of the logarithmic error growing linearly with the forecasting horizon at a typical rate of 2.5% per year. These results have implications for theories of technological change, and assessments of candidate technologies and policies for climate change mitigation. PMID:23468837

  6. Statistical basis for predicting technological progress.

    Directory of Open Access Journals (Sweden)

    Béla Nagy

    Full Text Available Forecasting technological progress is of great interest to engineers, policy makers, and private investors. Several models have been proposed for predicting technological improvement, but how well do these models perform? An early hypothesis made by Theodore Wright in 1936 is that cost decreases as a power law of cumulative production. An alternative hypothesis is Moore's law, which can be generalized to say that technologies improve exponentially with time. Other alternatives were proposed by Goddard, Sinclair et al., and Nordhaus. These hypotheses have not previously been rigorously tested. Using a new database on the cost and production of 62 different technologies, which is the most expansive of its kind, we test the ability of six different postulated laws to predict future costs. Our approach involves hindcasting and developing a statistical model to rank the performance of the postulated laws. Wright's law produces the best forecasts, but Moore's law is not far behind. We discover a previously unobserved regularity that production tends to increase exponentially. A combination of an exponential decrease in cost and an exponential increase in production would make Moore's law and Wright's law indistinguishable, as originally pointed out by Sahal. We show for the first time that these regularities are observed in data to such a degree that the performance of these two laws is nearly the same. Our results show that technological progress is forecastable, with the square root of the logarithmic error growing linearly with the forecasting horizon at a typical rate of 2.5% per year. These results have implications for theories of technological change, and assessments of candidate technologies and policies for climate change mitigation.

  7. Wind Resource Assessment and Forecast Planning with Neural Networks

    Directory of Open Access Journals (Sweden)

    Nicolus K. Rotich

    2014-06-01

    Full Text Available In this paper we built three types of artificial neural networks, namely: Feed forward networks, Elman networks and Cascade forward networks, for forecasting wind speeds and directions. A similar network topology was used for all the forecast horizons, regardless of the model type. All the models were then trained with real data of collected wind speeds and directions over a period of two years in the municipal of Puumala, Finland. Up to 70th percentile of the data was used for training, validation and testing, while 71–85th percentile was presented to the trained models for validation. The model outputs were then compared to the last 15% of the original data, by measuring the statistical errors between them. The feed forward networks returned the lowest errors for wind speeds. Cascade forward networks gave the lowest errors for wind directions; Elman networks returned the lowest errors when used for short term forecasting.

  8. Empirical seasonal forecasts of the NAO

    Science.gov (United States)

    Sanchezgomez, E.; Ortizbevia, M.

    2003-04-01

    We present here seasonal forecasts of the North Atlantic Oscillation (NAO) issued from ocean predictors with an empirical procedure. The Singular Values Decomposition (SVD) of the cross-correlation matrix between predictor and predictand fields at the lag used for the forecast lead is at the core of the empirical model. The main predictor field are sea surface temperature anomalies, although sea ice cover anomalies are also used. Forecasts are issued in probabilistic form. The model is an improvement over a previous version (1), where Sea Level Pressure Anomalies were first forecast, and the NAO Index built from this forecast field. Both correlation skill between forecast and observed field, and number of forecasts that hit the correct NAO sign, are used to assess the forecast performance , usually above those values found in the case of forecasts issued assuming persistence. For certain seasons and/or leads, values of the skill are above the .7 usefulness treshold. References (1) SanchezGomez, E. and Ortiz Bevia M., 2002, Estimacion de la evolucion pluviometrica de la Espana Seca atendiendo a diversos pronosticos empiricos de la NAO, in 'El Agua y el Clima', Publicaciones de la AEC, Serie A, N 3, pp 63-73, Palma de Mallorca, Spain

  9. Information technology resources assessment

    Energy Technology Data Exchange (ETDEWEB)

    Stevens, D.F. [ed.

    1992-01-01

    This year`s Information Technology Resources Assessment (ITRA) is something of a departure from traditional practice. Past assessments have concentrated on developments in fundamental technology, particularly with respect to hardware. They form an impressive chronicle of decreasing cycle times, increasing densities, decreasing costs (or, equivalently, increasing capacity and capability per dollar spent), and new system architectures, with a leavening of operating systems and languages. Past assessments have aimed -- and succeeded -- at putting information technology squarely in the spotlight; by contrast, in the first part of this assessment, we would like to move it to the background, and encourage the reader to reflect less on the continuing technological miracles of miniaturization in space and time and more on the second- and third-order implications of some possible workplace applications of these miracles. This Information Technology Resources Assessment is intended to provide a sense of technological direction for planners in projecting the hardware, software, and human resources necessary to support the diverse IT requirements of the various components of the DOE community. It is also intended to provide a sense of our new understanding of the place of IT in our organizations.

  10. Information technology resources assessment

    Energy Technology Data Exchange (ETDEWEB)

    Stevens, D.F. (ed.)

    1992-01-01

    This year's Information Technology Resources Assessment (ITRA) is something of a departure from traditional practice. Past assessments have concentrated on developments in fundamental technology, particularly with respect to hardware. They form an impressive chronicle of decreasing cycle times, increasing densities, decreasing costs (or, equivalently, increasing capacity and capability per dollar spent), and new system architectures, with a leavening of operating systems and languages. Past assessments have aimed -- and succeeded -- at putting information technology squarely in the spotlight; by contrast, in the first part of this assessment, we would like to move it to the background, and encourage the reader to reflect less on the continuing technological miracles of miniaturization in space and time and more on the second- and third-order implications of some possible workplace applications of these miracles. This Information Technology Resources Assessment is intended to provide a sense of technological direction for planners in projecting the hardware, software, and human resources necessary to support the diverse IT requirements of the various components of the DOE community. It is also intended to provide a sense of our new understanding of the place of IT in our organizations.

  11. Technology assessment of thermal treatment technologies using ORWARE

    International Nuclear Information System (INIS)

    Assefa, G.; Eriksson, O.; Frostell, B.

    2005-01-01

    A technology assessment of thermal treatment technologies for wastes was performed in the form of scenarios of chains of technologies. The Swedish assessment tool, ORWARE, was used for the assessment. The scenarios of chains of thermal technologies assessed were gasification with catalytic combustion, gasification with flame combustion, incineration and landfilling. The landfilling scenario was used as a reference for comparison. The technologies were assessed from ecological and economic points of view. The results are presented in terms of global warming potential, acidification potential, eutrophication potential, consumption of primary energy carriers and welfare costs. From the simulations, gasification followed by catalytic combustion with energy recovery in a combined cycle appeared to be the most competitive technology from an ecological point of view. On the other hand, this alternative was more expensive than incineration. A sensitivity analysis was done regarding electricity prices to show which technology wins at what value of the unit price of electricity (SEK/kW h). Within this study, it was possible to make a comparison both between a combined cycle and a Rankine cycle (a system pair) and at the same time between flame combustion and catalytic combustion (a technology pair). To use gasification just as a treatment technology is not more appealing than incineration, but the possibility of combining gasification with a combined cycle is attractive in terms of electricity production. This research was done in connection with an empirical R and D work on both gasification of waste and catalytic combustion of the gasified waste at the Division of Chemical Technology, Royal Institute of Technology (KTH), Sweden

  12. Next-generation probabilistic seismicity forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Hiemer, S.

    2014-07-01

    The development of probabilistic seismicity forecasts is one of the most important tasks of seismologists at present time. Such forecasts form the basis of probabilistic seismic hazard assessment, a widely used approach to generate ground motion exceedance maps. These hazard maps guide the development of building codes, and in the absence of the ability to deterministically predict earthquakes, good building and infrastructure planning is key to prevent catastrophes. Probabilistic seismicity forecasts are models that specify the occurrence rate of earthquakes as a function of space, time and magnitude. The models presented in this thesis are time-invariant mainshock occurrence models. Accordingly, the reliable estimation of the spatial and size distribution of seismicity are of crucial importance when constructing such probabilistic forecasts. Thereby we focus on data-driven approaches to infer these distributions, circumventing the need for arbitrarily chosen external parameters and subjective expert decisions. Kernel estimation has been shown to appropriately transform discrete earthquake locations into spatially continuous probability distributions. However, we show that neglecting the information from fault networks constitutes a considerable shortcoming and thus limits the skill of these current seismicity models. We present a novel earthquake rate forecast that applies the kernel-smoothing method to both past earthquake locations and slip rates on mapped crustal faults applied to Californian and European data. Our model is independent from biases caused by commonly used non-objective seismic zonations, which impose artificial borders of activity that are not expected in nature. Studying the spatial variability of the seismicity size distribution is of great importance. The b-value of the well-established empirical Gutenberg-Richter model forecasts the rates of hazard-relevant large earthquakes based on the observed rates of abundant small events. We propose a

  13. Next-generation probabilistic seismicity forecasting

    International Nuclear Information System (INIS)

    Hiemer, S.

    2014-01-01

    The development of probabilistic seismicity forecasts is one of the most important tasks of seismologists at present time. Such forecasts form the basis of probabilistic seismic hazard assessment, a widely used approach to generate ground motion exceedance maps. These hazard maps guide the development of building codes, and in the absence of the ability to deterministically predict earthquakes, good building and infrastructure planning is key to prevent catastrophes. Probabilistic seismicity forecasts are models that specify the occurrence rate of earthquakes as a function of space, time and magnitude. The models presented in this thesis are time-invariant mainshock occurrence models. Accordingly, the reliable estimation of the spatial and size distribution of seismicity are of crucial importance when constructing such probabilistic forecasts. Thereby we focus on data-driven approaches to infer these distributions, circumventing the need for arbitrarily chosen external parameters and subjective expert decisions. Kernel estimation has been shown to appropriately transform discrete earthquake locations into spatially continuous probability distributions. However, we show that neglecting the information from fault networks constitutes a considerable shortcoming and thus limits the skill of these current seismicity models. We present a novel earthquake rate forecast that applies the kernel-smoothing method to both past earthquake locations and slip rates on mapped crustal faults applied to Californian and European data. Our model is independent from biases caused by commonly used non-objective seismic zonations, which impose artificial borders of activity that are not expected in nature. Studying the spatial variability of the seismicity size distribution is of great importance. The b-value of the well-established empirical Gutenberg-Richter model forecasts the rates of hazard-relevant large earthquakes based on the observed rates of abundant small events. We propose a

  14. On the reliability of seasonal climate forecasts

    Science.gov (United States)

    Weisheimer, A.; Palmer, T. N.

    2014-01-01

    Seasonal climate forecasts are being used increasingly across a range of application sectors. A recent UK governmental report asked: how good are seasonal forecasts on a scale of 1–5 (where 5 is very good), and how good can we expect them to be in 30 years time? Seasonal forecasts are made from ensembles of integrations of numerical models of climate. We argue that ‘goodness’ should be assessed first and foremost in terms of the probabilistic reliability of these ensemble-based forecasts; reliable inputs are essential for any forecast-based decision-making. We propose that a ‘5’ should be reserved for systems that are not only reliable overall, but where, in particular, small ensemble spread is a reliable indicator of low ensemble forecast error. We study the reliability of regional temperature and precipitation forecasts of the current operational seasonal forecast system of the European Centre for Medium-Range Weather Forecasts, universally regarded as one of the world-leading operational institutes producing seasonal climate forecasts. A wide range of ‘goodness’ rankings, depending on region and variable (with summer forecasts of rainfall over Northern Europe performing exceptionally poorly) is found. Finally, we discuss the prospects of reaching ‘5’ across all regions and variables in 30 years time. PMID:24789559

  15. Operational forecasting of human-biometeorological conditions

    Science.gov (United States)

    Giannaros, T. M.; Lagouvardos, K.; Kotroni, V.; Matzarakis, A.

    2018-03-01

    This paper presents the development of an operational forecasting service focusing on human-biometeorological conditions. The service is based on the coupling of numerical weather prediction models with an advanced human-biometeorological model. Human thermal perception and stress forecasts are issued on a daily basis for Greece, in both point and gridded format. A user-friendly presentation approach is adopted for communicating the forecasts to the public via the worldwide web. The development of the presented service highlights the feasibility of replacing standard meteorological parameters and/or indices used in operational weather forecasting activities for assessing the thermal environment. This is of particular significance for providing effective, human-biometeorology-oriented, warnings for both heat waves and cold outbreaks.

  16. Singularity hypotheses a scientific and philosophical assessment

    CERN Document Server

    Moor, James; Søraker, Johnny; Steinhart, Eric

    2012-01-01

    Singularity Hypotheses: A Scientific and Philosophical Assessment offers authoritative, jargon-free essays and critical commentaries on accelerating technological progress and the notion of technological singularity. It focuses on conjectures about the intelligence explosion, transhumanism, and whole brain emulation. Recent years have seen a plethora of forecasts about the profound, disruptive impact that is likely to result from further progress in these areas. Many commentators however doubt the scientific rigor of these forecasts, rejecting them as speculative and unfounded. We therefore invited prominent computer scientists, physicists, philosophers, biologists, economists and other thinkers to assess the singularity hypotheses. Their contributions go beyond speculation, providing deep insights into the main issues and a balanced picture of the debate.

  17. Operational skill assessment of the IBI-MFC Ocean Forecasting System within the frame of the CMEMS.

    Science.gov (United States)

    Lorente Jimenez, Pablo; Garcia-Sotillo, Marcos; Amo-Balandron, Arancha; Aznar Lecocq, Roland; Perez Gomez, Begoña; Levier, Bruno; Alvarez-Fanjul, Enrique

    2016-04-01

    Since operational ocean forecasting systems (OOFSs) are increasingly used as tools to support high-stakes decision-making for coastal management, a rigorous skill assessment of model performance becomes essential. In this context, the IBI-MFC (Iberia-Biscay-Ireland Monitoring & Forecasting Centre) has been providing daily ocean model estimates and forecasts for the IBI regional seas since 2011, first in the frame of MyOcean projects and later as part of the Copernicus Marine Environment Monitoring Service (CMEMS). A comprehensive web validation tool named NARVAL (North Atlantic Regional VALidation) has been developed to routinely monitor IBI performance and to evaluate model's veracity and prognostic capabilities. Three-dimensional comparisons are carried out on a different time basis ('online mode' - daily verifications - and 'delayed mode' - for longer time periods -) using a broad variety of in-situ (buoys, tide-gauges, ARGO-floats, drifters and gliders) and remote-sensing (satellite and HF radars) observational sources as reference fields to validate against the NEMO model solution. Product quality indicators and meaningful skill metrics are automatically computed not only averaged over the entire IBI domain but also over specific sub-regions of particular interest from a user perspective (i.e. coastal or shelf areas) in order to determine IBI spatial and temporal uncertainty levels. A complementary aspect of NARVAL web tool is the intercomparison of different CMEMS forecast model solutions in overlapping areas. Noticeable efforts are in progress in order to quantitatively assess the quality and consistency of nested system outputs by setting up specific intercomparison exercises on different temporal and spatial scales, encompassing global configurations (CMEMS Global system), regional applications (NWS and MED ones) and local high-resolution coastal models (i.e. the PdE SAMPA system in the Gibraltar Strait). NARVAL constitutes a powerful approach to increase

  18. House Price Forecasts, Forecaster Herding, and the Recent Crisis

    DEFF Research Database (Denmark)

    Stadtmann, Georg; Pierdzioch; Ruelke

    2013-01-01

    We used the Wall Street Journal survey data for the period 2006–2012 to analyze whether forecasts of house prices and housing starts provide evidence of (anti-)herding of forecasters. Forecasts are consistent with herding (anti-herding) of forecasters if forecasts are biased towards (away from) t......) the consensus forecast. We found that anti-herding is prevalent among forecasters of house prices. We also report that, following the recent crisis, the prevalence of forecaster anti-herding seems to have changed over time....

  19. Operational hydrological forecasting in Bavaria. Part II: Ensemble forecasting

    Science.gov (United States)

    Ehret, U.; Vogelbacher, A.; Moritz, K.; Laurent, S.; Meyer, I.; Haag, I.

    2009-04-01

    In part I of this study, the operational flood forecasting system in Bavaria and an approach to identify and quantify forecast uncertainty was introduced. The approach is split into the calculation of an empirical 'overall error' from archived forecasts and the calculation of an empirical 'model error' based on hydrometeorological forecast tests, where rainfall observations were used instead of forecasts. The 'model error' can especially in upstream catchments where forecast uncertainty is strongly dependent on the current predictability of the atrmosphere be superimposed on the spread of a hydrometeorological ensemble forecast. In Bavaria, two meteorological ensemble prediction systems are currently tested for operational use: the 16-member COSMO-LEPS forecast and a poor man's ensemble composed of DWD GME, DWD Cosmo-EU, NCEP GFS, Aladin-Austria, MeteoSwiss Cosmo-7. The determination of the overall forecast uncertainty is dependent on the catchment characteristics: 1. Upstream catchment with high influence of weather forecast a) A hydrological ensemble forecast is calculated using each of the meteorological forecast members as forcing. b) Corresponding to the characteristics of the meteorological ensemble forecast, each resulting forecast hydrograph can be regarded as equally likely. c) The 'model error' distribution, with parameters dependent on hydrological case and lead time, is added to each forecast timestep of each ensemble member d) For each forecast timestep, the overall (i.e. over all 'model error' distribution of each ensemble member) error distribution is calculated e) From this distribution, the uncertainty range on a desired level (here: the 10% and 90% percentile) is extracted and drawn as forecast envelope. f) As the mean or median of an ensemble forecast does not necessarily exhibit meteorologically sound temporal evolution, a single hydrological forecast termed 'lead forecast' is chosen and shown in addition to the uncertainty bounds. This can be

  20. Assessing existing drought monitoring and forecasting capacities, mitigation and adaptation practices in Africa

    Science.gov (United States)

    Nyabeze, W. R.; Dlamini, L.; Lahlou, O.; Imani, Y.; Alaoui, S. B.; Vermooten, J. S. A.

    2012-04-01

    Drought is one of the major natural hazards in many parts of the world, including Africa and some regions in Europe. Drought events have resulted in extensive damages to livelihoods, environment and economy. In 2011, a consortium consisting of 19 organisations from both Africa and Europe started a project (DEWFORA) aimed at developing a framework for the provision of early warning and response through drought impact mitigation for Africa. This framework covers the whole chain from monitoring and vulnerability assessment to forecasting, warning, response and knowledge dissemination. This paper presents the first results of the capacity assessment of drought monitoring and forecasting systems in Africa, the existing institutional frameworks and drought mitigation and adaptation practices. Its focus is particularly on the historical drought mitigation and adaptation actions identified in the North Africa - Maghreb Region (Morocco, Algeria and Tunisia) and in the Southern Africa - Limpopo Basin. This is based on an extensive review of historical drought experiences. From the 1920's to 2009, the study identified 37 drought seasons in the North African - Maghreb Region and 33 drought seasons in the Southern Africa - Limpopo Basin. Existing literature tends to capture the spatial extent of drought at national and administrative scale in great detail. This is driven by the need to map drought impacts (food shortage, communities affected) in order to inform drought relief efforts (short-term drought mitigation measures). However, the mapping of drought at catchment scale (hydrological unit), required for longer-term measures, is not well documented. At regional level, both in North Africa and Southern Africa, two organisations are involved in drought monitoring and forecasting, while at national level 22 organisations are involved in North Africa and 37 in Southern Africa. Regarding drought related mitigation actions, the inventory shows that the most common actions

  1. Health technology assessment in Finland

    DEFF Research Database (Denmark)

    Mäkelä, Marjukka; Roine, Risto P

    2010-01-01

    Since the 1990s, health policy makers in Finland have been supportive of evidence-based medicine and approaches to implement its results. The Finnish Office for Health Technology Assessment (Finohta) has grown from a small start in 1995 to a medium-sized health technology assessment (HTA) agency,...... findings. The Managed Uptake of Medical Methods program links the hospital districts to agree on introduction of technologies. The Ohtanen database provides Finnish-language summaries of major assessments made in other countries.......Since the 1990s, health policy makers in Finland have been supportive of evidence-based medicine and approaches to implement its results. The Finnish Office for Health Technology Assessment (Finohta) has grown from a small start in 1995 to a medium-sized health technology assessment (HTA) agency......, with special responsibility in providing assessments to underpin national policies in screening. External evaluations enhanced the rapid growth. In the Finnish environment, decision making on health technologies is extremely decentralized, so Finohta has developed some practical tools for implementing HTA...

  2. House Price Forecasts, Forecaster Herding, and the Recent Crisis

    Directory of Open Access Journals (Sweden)

    Christian Pierdzioch

    2012-11-01

    Full Text Available We used the Wall Street Journal survey data for the period 2006–2012 to analyze whether forecasts of house prices and housing starts provide evidence of (anti-herding of forecasters. Forecasts are consistent with herding (anti-herding of forecasters if forecasts are biased towards (away from the consensus forecast. We found that anti-herding is prevalent among forecasters of house prices. We also report that, following the recent crisis, the prevalence of forecaster anti-herding seems to have changed over time.

  3. The weather forecasting in Colombia: Science plus Art

    International Nuclear Information System (INIS)

    Gonzalez Marentes, Humberto

    2006-01-01

    The presentation intends to show briefly and rapidly the progress weather forecasting science has undergone times until today. Undoubtedly, there has been an impressive technological advances, more data better models, better representations of the physics of the atmosphere; however for the case of the low latitude countries, there are still some problems to resolve concerning the local prediction that deserve more research and more data to be included in the models. As these limitations subsist, the subjective knowledge and the experience of the duty forecaster remain valuable. The presentation is also useful to summarize how IDEAM prepares short weather forecasts

  4. Value of Improved Wind Power Forecasting in the Western Interconnection (Poster)

    Energy Technology Data Exchange (ETDEWEB)

    Hodge, B.

    2013-12-01

    Wind power forecasting is a necessary and important technology for incorporating wind power into the unit commitment and dispatch process. It is expected to become increasingly important with higher renewable energy penetration rates and progress toward the smart grid. There is consensus that wind power forecasting can help utility operations with increasing wind power penetration; however, there is far from a consensus about the economic value of improved forecasts. This work explores the value of improved wind power forecasting in the Western Interconnection of the United States.

  5. Solid low-level waste forecasting guide

    International Nuclear Information System (INIS)

    Templeton, K.J.; Dirks, L.L.

    1995-03-01

    Guidance for forecasting solid low-level waste (LLW) on a site-wide basis is described in this document. Forecasting is defined as an approach for collecting information about future waste receipts. The forecasting approach discussed in this document is based solely on hanford's experience within the last six years. Hanford's forecasting technique is not a statistical forecast based upon past receipts. Due to waste generator mission changes, startup of new facilities, and waste generator uncertainties, statistical methods have proven to be inadequate for the site. It is recommended that an approach similar to Hanford's annual forecasting strategy be implemented at each US Department of Energy (DOE) installation to ensure that forecast data are collected in a consistent manner across the DOE complex. Hanford's forecasting strategy consists of a forecast cycle that can take 12 to 30 months to complete. The duration of the cycle depends on the number of LLW generators and staff experience; however, the duration has been reduced with each new cycle. Several uncertainties are associated with collecting data about future waste receipts. Volume, shipping schedule, and characterization data are often reported as estimates with some level of uncertainty. At Hanford, several methods have been implemented to capture the level of uncertainty. Collection of a maximum and minimum volume range has been implemented as well as questionnaires to assess the relative certainty in the requested data

  6. Environmental noise forecasting based on support vector machine

    Science.gov (United States)

    Fu, Yumei; Zan, Xinwu; Chen, Tianyi; Xiang, Shihan

    2018-01-01

    As an important pollution source, the noise pollution is always the researcher's focus. Especially in recent years, the noise pollution is seriously harmful to the human beings' environment, so the research about the noise pollution is a very hot spot. Some noise monitoring technologies and monitoring systems are applied in the environmental noise test, measurement and evaluation. But, the research about the environmental noise forecasting is weak. In this paper, a real-time environmental noise monitoring system is introduced briefly. This monitoring system is working in Mianyang City, Sichuan Province. It is monitoring and collecting the environmental noise about more than 20 enterprises in this district. Based on the large amount of noise data, the noise forecasting by the Support Vector Machine (SVM) is studied in detail. Compared with the time series forecasting model and the artificial neural network forecasting model, the SVM forecasting model has some advantages such as the smaller data size, the higher precision and stability. The noise forecasting results based on the SVM can provide the important and accuracy reference to the prevention and control of the environmental noise.

  7. Wind Power Forecasting Error Distributions: An International Comparison

    DEFF Research Database (Denmark)

    Hodge, Bri-Mathias; Lew, Debra; Milligan, Michael

    2012-01-01

    Wind power forecasting is essential for greater penetration of wind power into electricity systems. Because no wind forecasting system is perfect, a thorough understanding of the errors that may occur is a critical factor for system operation functions, such as the setting of operating reserve...... levels. This paper provides an international comparison of the distribution of wind power forecasting errors from operational systems, based on real forecast data. The paper concludes with an assessment of similarities and differences between the errors observed in different locations....

  8. Risk assessment research and technology assessment

    International Nuclear Information System (INIS)

    Albach, H.; Schade, D.; Sinn, H.

    1991-01-01

    The concepts and approaches for technology assessment, the targets and scientific principles, as well as recognizable deficits and recommendations concerning purposeful strategies for the promotion of this research field require a dialog between those concerned. Conception, deficits, and the necessary measures for risk assessment research and technology assessment were discussed as well as ethical aspects. The problematic nature of using organisms altered through genetic engineering in the open land, traffic and transport, site restoration, nuclear energy, and isotope applications were subjects particularly dealt with. (DG) [de

  9. A review of forecasting models for new products

    Directory of Open Access Journals (Sweden)

    Marta Mas-Machuca

    2014-02-01

    Full Text Available Purpose. The main objective of this article is to present an up-to-date review of new product forecasting techniques. Design/methodology/approach: A systematic review of forecasting journals was carried out using the ISI-Web of Knowledge database. Several articles were retrieved and examined, and forecasting techniques relevant to this study were selected and assessed. Findings: The strengths, weaknesses and applications of the main forecasting models are discussed to examine trends and set future challenges. Research limitations/implications: A theoretical reference framework for forecasting techniques classified into judgmental, consumer/market research, cause-effect and artificial intelligence is proposed. Future research can assess these models qualitatively. Practical implications: Companies are currently motivated to launch new products and thus attract new customers to expand their market share.  In order to reduce uncertainty and risk, many companies go to extra lengths to forecast sales accurately using several techniques. Originality/value: This article outlines new lines of research on the improvement of new product performance which will aid managers in decision making and allow companies to sustain their competitive advantages in this challenging world.

  10. The intersections between TRIZ and forecasting methodology

    Directory of Open Access Journals (Sweden)

    Georgeta BARBULESCU

    2010-12-01

    Full Text Available The authors’ intention is to correlate the basic knowledge in using the TRIZ methodology (Theory of Inventive Problem Solving or in Russian: Teoriya Resheniya Izobretatelskikh Zadatch as a problem solving tools meant to help the decision makers to perform more significant forecasting exercises. The idea is to identify the TRIZ features and instruments (40 inventive principles, i.e. for putting in evidence the noise and signal problem, for trend identification (qualitative and quantitative tendencies and support tools in technological forecasting, to make the decision-makers able to refine and to increase the level of confidence in the forecasting results. The interest in connecting TRIZ to forecasting methodology, nowadays, relates to the massive application of TRIZ methods and techniques for engineering system development world-wide and in growing application of TRIZ’s concepts and paradigms for improvements of non-engineering systems (including the business and economic applications.

  11. Assessing nanocellulose developments using science and technology indicators

    Directory of Open Access Journals (Sweden)

    Douglas Henrique Milanez

    2013-06-01

    Full Text Available This research aims to examine scientific and technological trends of developments in nanocellulose based on scientometric and patent indicators obtained from the Science Citation Index and Derwent Innovations Index in 2001-2010. The overall nanocellulose activity indicators were compared to nanotechnology and other selected nanomaterials. Scientific and technological future developments in nanocellulose were forecasted using extrapolation growth curves and the main countries were also mapped. The results showed that nanocellulose publications and patent documents have increased rapidly over the last five years with an average growth rate higher than that of nanotechnology and fullerene. The USA, Japan, France, Sweden and Finland all played a significant role in nanocellulose development and the extrapolation growth curves suggested that nanocellulose scientific and technological activities are still emerging. Finally, the evidence from this study recommends monitoring nanocellulose S&T advances in the coming years.

  12. An Electrical Energy Consumption Monitoring and Forecasting System

    Directory of Open Access Journals (Sweden)

    J. L. Rojas-Renteria

    2016-10-01

    Full Text Available Electricity consumption is currently an issue of great interest for power companies that need an as much as accurate profile for controlling the installed systems but also for designing future expansions and alterations. Detailed monitoring has proved to be valuable for both power companies and consumers. Further, as smart grid technology is bound to result to increasingly flexible rates, an accurate forecast is bound to prove valuable in the future. In this paper, a monitoring and forecasting system is investigated. The monitoring system was installed in an actual building and the recordings were used to design and evaluate the forecasting system, based on an artificial neural network. Results show that the system can provide detailed monitoring and also an accurate forecast for a building’s consumption.

  13. Should we use seasonnal meteorological ensemble forecasts for hydrological forecasting? A case study for nordic watersheds in Canada.

    Science.gov (United States)

    Bazile, Rachel; Boucher, Marie-Amélie; Perreault, Luc; Leconte, Robert; Guay, Catherine

    2017-04-01

    Hydro-electricity is a major source of energy for many countries throughout the world, including Canada. Long lead-time streamflow forecasts are all the more valuable as they help decision making and dam management. Different techniques exist for long-term hydrological forecasting. Perhaps the most well-known is 'Extended Streamflow Prediction' (ESP), which considers past meteorological scenarios as possible, often equiprobable, future scenarios. In the ESP framework, those past-observed meteorological scenarios (climatology) are used in turn as the inputs of a chosen hydrological model to produce ensemble forecasts (one member corresponding to each year in the available database). Many hydropower companies, including Hydro-Québec (province of Quebec, Canada) use variants of the above described ESP system operationally for long-term operation planning. The ESP system accounts for the hydrological initial conditions and for the natural variability of the meteorological variables. However, it cannot consider the current initial state of the atmosphere. Climate models can help remedy this drawback. In the context of a changing climate, dynamical forecasts issued from climate models seem to be an interesting avenue to improve upon the ESP method and could help hydropower companies to adapt their management practices to an evolving climate. Long-range forecasts from climate models can also be helpful for water management at locations where records of past meteorological conditions are short or nonexistent. In this study, we compare 7-month hydrological forecasts obtained from climate model outputs to an ESP system. The ESP system mimics the one used operationally at Hydro-Québec. The dynamical climate forecasts are produced by the European Center for Medium range Weather Forecasts (ECMWF) System4. Forecasts quality is assessed using numerical scores such as the Continuous Ranked Probability Score (CRPS) and the Ignorance score and also graphical tools such as the

  14. Flood forecasting and uncertainty of precipitation forecasts

    International Nuclear Information System (INIS)

    Kobold, Mira; Suselj, Kay

    2004-01-01

    The timely and accurate flood forecasting is essential for the reliable flood warning. The effectiveness of flood warning is dependent on the forecast accuracy of certain physical parameters, such as the peak magnitude of the flood, its timing, location and duration. The conceptual rainfall - runoff models enable the estimation of these parameters and lead to useful operational forecasts. The accurate rainfall is the most important input into hydrological models. The input for the rainfall can be real time rain-gauges data, or weather radar data, or meteorological forecasted precipitation. The torrential nature of streams and fast runoff are characteristic for the most of the Slovenian rivers. Extensive damage is caused almost every year- by rainstorms affecting different regions of Slovenia' The lag time between rainfall and runoff is very short for Slovenian territory and on-line data are used only for now casting. Forecasted precipitations are necessary for hydrological forecast for some days ahead. ECMWF (European Centre for Medium-Range Weather Forecasts) gives general forecast for several days ahead while more detailed precipitation data with limited area ALADIN/Sl model are available for two days ahead. There is a certain degree of uncertainty using such precipitation forecasts based on meteorological models. The variability of precipitation is very high in Slovenia and the uncertainty of ECMWF predicted precipitation is very large for Slovenian territory. ECMWF model can predict precipitation events correctly, but underestimates amount of precipitation in general The average underestimation is about 60% for Slovenian region. The predictions of limited area ALADIN/Si model up to; 48 hours ahead show greater applicability in hydrological forecasting. The hydrological models are sensitive to precipitation input. The deviation of runoff is much bigger than the rainfall deviation. Runoff to rainfall error fraction is about 1.6. If spatial and time distribution

  15. Information Technology and Literacy Assessment.

    Science.gov (United States)

    Balajthy, Ernest

    2002-01-01

    Compares technology predictions from around 1989 with the technology of 2002. Discusses the place of computer-based assessment today, computer-scored testing, computer-administered formal assessment, Internet-based formal assessment, computerized adaptive tests, placement tests, informal assessment, electronic portfolios, information management,…

  16. Development of Advanced Life Cycle Costing Methods for Technology Benefit/Cost/Risk Assessment

    Science.gov (United States)

    Yackovetsky, Robert (Technical Monitor)

    2002-01-01

    The overall objective of this three-year grant is to provide NASA Langley's System Analysis Branch with improved affordability tools and methods based on probabilistic cost assessment techniques. In order to accomplish this objective, the Aerospace Systems Design Laboratory (ASDL) needs to pursue more detailed affordability, technology impact, and risk prediction methods and to demonstrate them on variety of advanced commercial transports. The affordability assessment, which is a cornerstone of ASDL methods, relies on the Aircraft Life Cycle Cost Analysis (ALCCA) program originally developed by NASA Ames Research Center and enhanced by ASDL. This grant proposed to improve ALCCA in support of the project objective by updating the research, design, test, and evaluation cost module, as well as the engine development cost module. Investigations into enhancements to ALCCA include improved engine development cost, process based costing, supportability cost, and system reliability with airline loss of revenue for system downtime. A probabilistic, stand-alone version of ALCCA/FLOPS will also be developed under this grant in order to capture the uncertainty involved in technology assessments. FLOPS (FLight Optimization System program) is an aircraft synthesis and sizing code developed by NASA Langley Research Center. This probabilistic version of the coupled program will be used within a Technology Impact Forecasting (TIF) method to determine what types of technologies would have to be infused in a system in order to meet customer requirements. A probabilistic analysis of the CER's (cost estimating relationships) within ALCCA will also be carried out under this contract in order to gain some insight as to the most influential costs and the impact that code fidelity could have on future RDS (Robust Design Simulation) studies.

  17. Technology Performance Level Assessment Methodology.

    Energy Technology Data Exchange (ETDEWEB)

    Roberts, Jesse D.; Bull, Diana L; Malins, Robert Joseph; Costello, Ronan Patrick; Aurelien Babarit; Kim Nielsen; Claudio Bittencourt Ferreira; Ben Kennedy; Kathryn Dykes; Jochem Weber

    2017-04-01

    The technology performance level (TPL) assessments can be applied at all technology development stages and associated technology readiness levels (TRLs). Even, and particularly, at low TRLs the TPL assessment is very effective as it, holistically, considers a wide range of WEC attributes that determine the techno-economic performance potential of the WEC farm when fully developed for commercial operation. The TPL assessment also highlights potential showstoppers at the earliest possible stage of the WEC technology development. Hence, the TPL assessment identifies the technology independent “performance requirements.” In order to achieve a successful solution, the entirety of the performance requirements within the TPL must be considered because, in the end, all the stakeholder needs must be achieved. The basis for performing a TPL assessment comes from the information provided in a dedicated format, the Technical Submission Form (TSF). The TSF requests information from the WEC developer that is required to answer the questions posed in the TPL assessment document.

  18. Life cycle assessment of forecasting scenarios for urban water management: A first implementation of the WaLA model on Paris suburban area.

    Science.gov (United States)

    Loubet, Philippe; Roux, Philippe; Guérin-Schneider, Laetitia; Bellon-Maurel, Véronique

    2016-03-01

    A framework and an associated modeling tool to perform life cycle assessment (LCA) of urban water system, namely the WaLA model, has been recently developed. In this paper, the WaLA model is applied to a real case study: the urban water system of the Paris suburban area, in France. It aims to verify the capacity of the model to provide environmental insights to stakeholder's issues related to future trends influencing the system (e.g., evolution of water demand, increasing water scarcity) or policy responses (e.g., choices of water resources and technologies). This is achieved by evaluating a baseline scenario for 2012 and several forecasting scenarios for 2022 and 2050. The scenarios are designed through the modeling tool WaLA, which is implemented in Simulink/Matlab: it combines components representing the different technologies, users and resources of the UWS. The life cycle inventories of the technologies and users components include water quantity and quality changes, specific operation (electricity, chemicals) and infrastructures data (construction materials). The methods selected for the LCIA are midpoint ILCD, midpoint water deprivation impacts at the sub-river basin scale, and endpoint Impact 2002+. The results of the baseline scenario show that wastewater treatment plants have the highest impacts compared to drinking water production and distribution, as traditionally encountered in LCA of UWS. The results of the forecasting scenarios show important changes in water deprivation impacts due to water management choices or effects of climate change. They also enable to identify tradeoffs with other impact categories and to compare several scenarios. It suggests the capacity of the model to deliver information for decision making about future policies. Copyright © 2015 Elsevier Ltd. All rights reserved.

  19. Decontamination technology assessment

    International Nuclear Information System (INIS)

    Allen, R.P.; Konzek, G.J.; Schneider, K.R.; Smith, R.I.

    1988-10-01

    This study identifies and technically assesses foreign decontamination and decommissioning (D and D) technology developments that may represent significant improvements over D and D technology currently available or under development in the United States. Technology need areas for nuclear power reactor decommissioning operations were identified and prioritized using the results of past light water reactor (LWR) decommissioning studies to quantitatively evaluate the potential for reducing cost and decommissioning worker radiation dose for each major decommissioning activity. Based on these identified needs, current foreign D and D technologies of potential interest to the US were identified through personal contacts and the collection and review of an extensive body of D and D literature. These technologies were then assessed qualitatively to evaluate their uniqueness, potential for a significant reduction in D and D costs and/or worker radiation dose, development status, and other factors affecting their value and applicability to US needs. 4 refs

  20. Operational aerosol and dust storm forecasting

    International Nuclear Information System (INIS)

    Westphal, D L; Curtis, C A; Liu, M; Walker, A L

    2009-01-01

    The U. S. Navy now conducts operational forecasting of aerosols and dust storms on global and regional scales. The Navy Aerosol Analysis and Prediction System (NAAPS) is run four times per day and produces 6-day forecasts of sulfate, smoke, dust and sea salt aerosol concentrations and visibility for the entire globe. The Coupled Ocean Atmosphere Mesoscale Prediction System (COAMPS (registered) ) is run twice daily for Southwest Asia and produces 3-day forecasts of dust, smoke, and visibility. The graphical output from these models is available on the Internet (www.nrlmry.navy.mil/aerosol/). The aerosol optical properties are calculated for each specie for each forecast output time and used for sea surface temperature (SST) retrieval corrections, regional electro-optical (EO) propagation assessments, and the development of satellite algorithms. NAAPS daily aerosol optical depth (AOD) values are compared with the Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) AOD values. Visibility forecasts are compared quantitatively with surface synoptic reports.

  1. Forecasting new product diffusion using both patent citation and web search traffic.

    Science.gov (United States)

    Lee, Won Sang; Choi, Hyo Shin; Sohn, So Young

    2018-01-01

    Accurate demand forecasting for new technology products is a key factor in the success of a business. We propose a way to forecasting a new product's diffusion through technology diffusion and interest diffusion. Technology diffusion and interest diffusion are measured by the volume of patent citations and web search traffic, respectively. We apply the proposed method to forecast the sales of hybrid cars and industrial robots in the US market. The results show that that technology diffusion, as represented by patent citations, can explain long-term sales for hybrid cars and industrial robots. On the other hand, interest diffusion, as represented by web search traffic, can help to improve the predictability of market sales of hybrid cars in the short-term. However, interest diffusion is difficult to explain the sales of industrial robots due to the different market characteristics. Finding indicates our proposed model can relatively well explain the diffusion of consumer goods.

  2. ASSESSMENT OF QUALITY OF INNOVATIVE TECHNOLOGIES

    Directory of Open Access Journals (Sweden)

    Larisa Alexejevna Ismagilova

    2016-12-01

    Full Text Available We consider the topical issue of implementation of innovative technologies in the aircraft engine building industry. In this industry, products with high reliability requirements are developed and mass-produced. These products combine the latest achievements of science and technology. To make a decision on implementation of innovative technologies, a comprehensive assessment is carried out. It affects the efficiency of the innovations realization. In connection with this, the assessment of quality of innovative technologies is a key aspect in the selection of technological processes for their implementation. Problems concerning assessment of the quality of new technologies and processes of production are considered in the suggested method with respect to new positions. The developed method of assessing the quality of innovative technologies stands out for formed system of the qualimetric characteristics ensuring the effectiveness, efficiency, adaptability of innovative technologies and processes. The feature of suggested system of assessment is that it is based on principles of matching and grouping of quality indicators of innovative technologies and the characteristics of technological processes. The indicators are assessed from the standpoint of feasibility, technologies competiveness and commercial demand of products. In this paper, we discuss the example of implementing the approach of assessing the quality of the innovative technology of high-tech products such as turbine aircraft engine.

  3. Net load forecasting for high renewable energy penetration grids

    International Nuclear Information System (INIS)

    Kaur, Amanpreet; Nonnenmacher, Lukas; Coimbra, Carlos F.M.

    2016-01-01

    We discuss methods for net load forecasting and their significance for operation and management of power grids with high renewable energy penetration. Net load forecasting is an enabling technology for the integration of microgrid fleets with the macrogrid. Net load represents the load that is traded between the grids (microgrid and utility grid). It is important for resource allocation and electricity market participation at the point of common coupling between the interconnected grids. We compare two inherently different approaches: additive and integrated net load forecast models. The proposed methodologies are validated on a microgrid with 33% annual renewable energy (solar) penetration. A heuristics based solar forecasting technique is proposed, achieving skill of 24.20%. The integrated solar and load forecasting model outperforms the additive model by 10.69% and the uncertainty range for the additive model is larger than the integrated model by 2.2%. Thus, for grid applications an integrated forecast model is recommended. We find that the net load forecast errors and the solar forecasting errors are cointegrated with a common stochastic drift. This is useful for future planning and modeling because the solar energy time-series allows to infer important features of the net load time-series, such as expected variability and uncertainty. - Highlights: • Net load forecasting methods for grids with renewable energy generation are discussed. • Integrated solar and load forecasting outperforms the additive model by 10.69%. • Net load forecasting reduces the uncertainty between the interconnected grids.

  4. Forecasting in the presence of expectations

    Science.gov (United States)

    Allen, R.; Zivin, J. G.; Shrader, J.

    2016-05-01

    Physical processes routinely influence economic outcomes, and actions by economic agents can, in turn, influence physical processes. This feedback creates challenges for forecasting and inference, creating the potential for complementarity between models from different academic disciplines. Using the example of prediction of water availability during a drought, we illustrate the potential biases in forecasts that only take part of a coupled system into account. In particular, we show that forecasts can alter the feedbacks between supply and demand, leading to inaccurate prediction about future states of the system. Although the example is specific to drought, the problem of feedback between expectations and forecast quality is not isolated to the particular model-it is relevant to areas as diverse as population assessments for conservation, balancing the electrical grid, and setting macroeconomic policy.

  5. Communicating uncertainty in hydrological forecasts: mission impossible?

    Science.gov (United States)

    Ramos, Maria-Helena; Mathevet, Thibault; Thielen, Jutta; Pappenberger, Florian

    2010-05-01

    Cascading uncertainty in meteo-hydrological modelling chains for forecasting and integrated flood risk assessment is an essential step to improve the quality of hydrological forecasts. Although the best methodology to quantify the total predictive uncertainty in hydrology is still debated, there is a common agreement that one must avoid uncertainty misrepresentation and miscommunication, as well as misinterpretation of information by users. Several recent studies point out that uncertainty, when properly explained and defined, is no longer unwelcome among emergence response organizations, users of flood risk information and the general public. However, efficient communication of uncertain hydro-meteorological forecasts is far from being a resolved issue. This study focuses on the interpretation and communication of uncertain hydrological forecasts based on (uncertain) meteorological forecasts and (uncertain) rainfall-runoff modelling approaches to decision-makers such as operational hydrologists and water managers in charge of flood warning and scenario-based reservoir operation. An overview of the typical flow of uncertainties and risk-based decisions in hydrological forecasting systems is presented. The challenges related to the extraction of meaningful information from probabilistic forecasts and the test of its usefulness in assisting operational flood forecasting are illustrated with the help of two case-studies: 1) a study on the use and communication of probabilistic flood forecasting within the European Flood Alert System; 2) a case-study on the use of probabilistic forecasts by operational forecasters from the hydroelectricity company EDF in France. These examples show that attention must be paid to initiatives that promote or reinforce the active participation of expert forecasters in the forecasting chain. The practice of face-to-face forecast briefings, focusing on sharing how forecasters interpret, describe and perceive the model output forecasted

  6. Demand Forecasting in the Smart Grid Paradigm: Features and Challenges

    Energy Technology Data Exchange (ETDEWEB)

    Khodayar, Mohammad E.; Wu, Hongyu

    2015-07-01

    Demand forecasting faces challenges that include a large volume of data, increasing number of factors that affect the demand profile, uncertainties in the generation profile of the distributed and renewable generation resources and lack of historical data. A hierarchical demand forecasting framework can incorporate the new technologies, customer behaviors and preferences, and environmental factors.

  7. A Hybrid Approach on Tourism Demand Forecasting

    Science.gov (United States)

    Nor, M. E.; Nurul, A. I. M.; Rusiman, M. S.

    2018-04-01

    Tourism has become one of the important industries that contributes to the country’s economy. Tourism demand forecasting gives valuable information to policy makers, decision makers and organizations related to tourism industry in order to make crucial decision and planning. However, it is challenging to produce an accurate forecast since economic data such as the tourism data is affected by social, economic and environmental factors. In this study, an equally-weighted hybrid method, which is a combination of Box-Jenkins and Artificial Neural Networks, was applied to forecast Malaysia’s tourism demand. The forecasting performance was assessed by taking the each individual method as a benchmark. The results showed that this hybrid approach outperformed the other two models

  8. Towards new success factors in technology intelligence evidence from a european benchmarking study

    OpenAIRE

    Schuh, Günther; Lau, Felix; Kabasci, Patrick; Bachmann, Heidi

    2017-01-01

    As a reaction to the fast changing, complex business environments of today, many technology-driven firms rely on technology intelligence - an integrated process of searching, assessing and disseminating relevant information and insights to decision makers within an organization. Despite this, many firms fail at assessing the relevant trends of their business appropriately. This paper addresses the underlying problem and examines antecedents of successful technology forecasting. Using the cons...

  9. Forecast Combinations

    OpenAIRE

    Timmermann, Allan G

    2005-01-01

    Forecast combinations have frequently been found in empirical studies to produce better forecasts on average than methods based on the ex-ante best individual forecasting model. Moreover, simple combinations that ignore correlations between forecast errors often dominate more refined combination schemes aimed at estimating the theoretically optimal combination weights. In this paper we analyse theoretically the factors that determine the advantages from combining forecasts (for example, the d...

  10. Forecaster Behaviour and Bias in Macroeconomic Forecasts

    OpenAIRE

    Roy Batchelor

    2007-01-01

    This paper documents the presence of systematic bias in the real GDP and inflation forecasts of private sector forecasters in the G7 economies in the years 1990–2005. The data come from the monthly Consensus Economics forecasting service, and bias is measured and tested for significance using parametric fixed effect panel regressions and nonparametric tests on accuracy ranks. We examine patterns across countries and forecasters to establish whether the bias reflects the inefficient use of i...

  11. Decontamination technology assessment

    International Nuclear Information System (INIS)

    Allen, R.P.; Konzek, G.J.; Schneider, K.J.; Smith, R.I.

    1988-01-01

    This study was conducted by the Pacific Northwest Laboratory (PNL) for the U.S. Department of Energy (DOE) to identify and technically assess foreign decontamination and decommissioning (D and D) technology developments that may represent significant improvements over D and D technology currently available or under development in the United States. Technology need areas for nuclear power reactor decommissioning operations were identified and prioritized using the results of past light water rector (LWR) decommissioning studies to quantitatively evaluate the potential for reducing cost and decommissioning worker radiation dose for each major decommissioning activity. Based on these identified needs, current foreign D and D technologies of potential interest to the U.S. were identified through personal contacts and the collection and review of an extensive body of D and D literature. These technologies were then assessed qualitatively to evaluate their uniqueness, potential for a significant reduction in D and D costs and/or worker radiation dose, development status, and other factors affecting their value and applicability to U.S. needs

  12. Inferential, non-parametric statistics to assess the quality of probabilistic forecast systems

    NARCIS (Netherlands)

    Maia, A.H.N.; Meinke, H.B.; Lennox, S.; Stone, R.C.

    2007-01-01

    Many statistical forecast systems are available to interested users. To be useful for decision making, these systems must be based on evidence of underlying mechanisms. Once causal connections between the mechanism and its statistical manifestation have been firmly established, the forecasts must

  13. The economic value of accurate wind power forecasting to utilities

    Energy Technology Data Exchange (ETDEWEB)

    Watson, S J [Rutherford Appleton Lab., Oxfordshire (United Kingdom); Giebel, G; Joensen, A [Risoe National Lab., Dept. of Wind Energy and Atmospheric Physics, Roskilde (Denmark)

    1999-03-01

    With increasing penetrations of wind power, the need for accurate forecasting is becoming ever more important. Wind power is by its very nature intermittent. For utility schedulers this presents its own problems particularly when the penetration of wind power capacity in a grid reaches a significant level (>20%). However, using accurate forecasts of wind power at wind farm sites, schedulers are able to plan the operation of conventional power capacity to accommodate the fluctuating demands of consumers and wind farm output. The results of a study to assess the value of forecasting at several potential wind farm sites in the UK and in the US state of Iowa using the Reading University/Rutherford Appleton Laboratory National Grid Model (NGM) are presented. The results are assessed for different types of wind power forecasting, namely: persistence, optimised numerical weather prediction or perfect forecasting. In particular, it will shown how the NGM has been used to assess the value of numerical weather prediction forecasts from the Danish Meteorological Institute model, HIRLAM, and the US Nested Grid Model, which have been `site tailored` by the use of the linearized flow model WA{sup s}P and by various Model output Statistics (MOS) and autoregressive techniques. (au)

  14. Evaluation of Wind Power Forecasts from the Vermont Weather Analytics Center and Identification of Improvements

    Energy Technology Data Exchange (ETDEWEB)

    Optis, Michael [National Renewable Energy Lab. (NREL), Golden, CO (United States); Scott, George N. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Draxl, Caroline [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2018-02-02

    The goal of this analysis was to assess the wind power forecast accuracy of the Vermont Weather Analytics Center (VTWAC) forecast system and to identify potential improvements to the forecasts. Based on the analysis at Georgia Mountain, the following recommendations for improving forecast performance were made: 1. Resolve the significant negative forecast bias in February-March 2017 (50% underprediction on average) 2. Improve the ability of the forecast model to capture the strong diurnal cycle of wind power 3. Add ability for forecast model to assess internal wake loss, particularly at sites where strong diurnal shifts in wind direction are present. Data availability and quality limited the robustness of this forecast assessment. A more thorough analysis would be possible given a longer period of record for the data (at least one full year), detailed supervisory control and data acquisition data for each wind plant, and more detailed information on the forecast system input data and methodologies.

  15. Maximizing Statistical Power When Verifying Probabilistic Forecasts of Hydrometeorological Events

    Science.gov (United States)

    DeChant, C. M.; Moradkhani, H.

    2014-12-01

    Hydrometeorological events (i.e. floods, droughts, precipitation) are increasingly being forecasted probabilistically, owing to the uncertainties in the underlying causes of the phenomenon. In these forecasts, the probability of the event, over some lead time, is estimated based on some model simulations or predictive indicators. By issuing probabilistic forecasts, agencies may communicate the uncertainty in the event occurring. Assuming that the assigned probability of the event is correct, which is referred to as a reliable forecast, the end user may perform some risk management based on the potential damages resulting from the event. Alternatively, an unreliable forecast may give false impressions of the actual risk, leading to improper decision making when protecting resources from extreme events. Due to this requisite for reliable forecasts to perform effective risk management, this study takes a renewed look at reliability assessment in event forecasts. Illustrative experiments will be presented, showing deficiencies in the commonly available approaches (Brier Score, Reliability Diagram). Overall, it is shown that the conventional reliability assessment techniques do not maximize the ability to distinguish between a reliable and unreliable forecast. In this regard, a theoretical formulation of the probabilistic event forecast verification framework will be presented. From this analysis, hypothesis testing with the Poisson-Binomial distribution is the most exact model available for the verification framework, and therefore maximizes one's ability to distinguish between a reliable and unreliable forecast. Application of this verification system was also examined within a real forecasting case study, highlighting the additional statistical power provided with the use of the Poisson-Binomial distribution.

  16. Forecast combinations

    OpenAIRE

    Aiolfi, Marco; Capistrán, Carlos; Timmermann, Allan

    2010-01-01

    We consider combinations of subjective survey forecasts and model-based forecasts from linear and non-linear univariate specifications as well as multivariate factor-augmented models. Empirical results suggest that a simple equal-weighted average of survey forecasts outperform the best model-based forecasts for a majority of macroeconomic variables and forecast horizons. Additional improvements can in some cases be gained by using a simple equal-weighted average of survey and model-based fore...

  17. Forecasting Canadian nuclear power station construction costs

    International Nuclear Information System (INIS)

    Keng, C.W.K.

    1985-01-01

    Because of the huge volume of capital required to construct a modern electric power generating station, investment decisions have to be made with as complete an understanding of the consequences of the decision as possible. This understanding must be provided by the evaluation of future situations. A key consideration in an evaluation is the financial component. This paper attempts to use an econometric method to forecast the construction costs escalation of a standard Canadian nuclear generating station (NGS). A brief review of the history of Canadian nuclear electric power is provided. The major components of the construction costs of a Canadian NGS are studied and summarized. A database is built and indexes are prepared. Based on these indexes, an econometric forecasting model is constructed using an apparently new econometric methodology of forecasting modelling. Forecasts for a period of 40 years are generated and applications (such as alternative scenario forecasts and range forecasts) to uncertainty assessment and/or decision-making are demonstrated. The indexes, the model, and the forecasts and their applications, to the best of the author's knowledge, are the first for Canadian NGS constructions. (author)

  18. Using inferred probabilities to measure the accuracy of imprecise forecasts

    Directory of Open Access Journals (Sweden)

    Paul Lehner

    2012-11-01

    Full Text Available Research on forecasting is effectively limited to forecasts that are expressed with clarity; which is to say that the forecasted event must be sufficiently well-defined so that it can be clearly resolved whether or not the event occurred and forecasts certainties are expressed as quantitative probabilities. When forecasts are expressed with clarity, then quantitative measures (scoring rules, calibration, discrimination, etc. can be used to measure forecast accuracy, which in turn can be used to measure the comparative accuracy of different forecasting methods. Unfortunately most real world forecasts are not expressed clearly. This lack of clarity extends to both the description of the forecast event and to the use of vague language to express forecast certainty. It is thus difficult to assess the accuracy of most real world forecasts, and consequently the accuracy the methods used to generate real world forecasts. This paper addresses this deficiency by presenting an approach to measuring the accuracy of imprecise real world forecasts using the same quantitative metrics routinely used to measure the accuracy of well-defined forecasts. To demonstrate applicability, the Inferred Probability Method is applied to measure the accuracy of forecasts in fourteen documents examining complex political domains. Key words: inferred probability, imputed probability, judgment-based forecasting, forecast accuracy, imprecise forecasts, political forecasting, verbal probability, probability calibration.

  19. Approaches to Assessing Technological Literacy

    Science.gov (United States)

    Pearson, Greg

    2006-01-01

    It is the conclusion of the Committee on Assessing Technological Literacy, a study panel appointed by the National Academy of Engineering and the National Research Council, that very little is known about what children or adults know, can do, and believe about technology. This is because the state of assessment related to technology--or, …

  20. Modeling and forecasting petroleum futures volatility

    International Nuclear Information System (INIS)

    Sadorsky, Perry

    2006-01-01

    Forecasts of oil price volatility are important inputs into macroeconometric models, financial market risk assessment calculations like value at risk, and option pricing formulas for futures contracts. This paper uses several different univariate and multivariate statistical models to estimate forecasts of daily volatility in petroleum futures price returns. The out-of-sample forecasts are evaluated using forecast accuracy tests and market timing tests. The TGARCH model fits well for heating oil and natural gas volatility and the GARCH model fits well for crude oil and unleaded gasoline volatility. Simple moving average models seem to fit well in some cases provided the correct order is chosen. Despite the increased complexity, models like state space, vector autoregression and bivariate GARCH do not perform as well as the single equation GARCH model. Most models out perform a random walk and there is evidence of market timing. Parametric and non-parametric value at risk measures are calculated and compared. Non-parametric models outperform the parametric models in terms of number of exceedences in backtests. These results are useful for anyone needing forecasts of petroleum futures volatility. (author)

  1. A Simplified Short Term Load Forecasting Method Based on Sequential Patterns

    DEFF Research Database (Denmark)

    Kouzelis, Konstantinos; Bak-Jensen, Birgitte; Mahat, Pukar

    2014-01-01

    Load forecasting is an essential part of a power system both for planning and daily operation purposes. As far as the latter is concerned, short term load forecasting has been broadly used at the transmission level. However, recent technological advancements and legislation have facilitated the i...... in comparison with an ARIMA model....

  2. Non-seismic tsunamis: filling the forecast gap

    Science.gov (United States)

    Moore, C. W.; Titov, V. V.; Spillane, M. C.

    2015-12-01

    Earthquakes are the generation mechanism in over 85% of tsunamis. However, non-seismic tsunamis, including those generated by meteorological events, landslides, volcanoes, and asteroid impacts, can inundate significant area and have a large far-field effect. The current National Oceanographic and Atmospheric Administration (NOAA) tsunami forecast system falls short in detecting these phenomena. This study attempts to classify the range of effects possible from these non-seismic threats, and to investigate detection methods appropriate for use in a forecast system. Typical observation platforms are assessed, including DART bottom pressure recorders and tide gauges. Other detection paths include atmospheric pressure anomaly algorithms for detecting meteotsunamis and the early identification of asteroids large enough to produce a regional hazard. Real-time assessment of observations for forecast use can provide guidance to mitigate the effects of a non-seismic tsunami.

  3. Operational hydrological forecasting in Bavaria. Part I: Forecast uncertainty

    Science.gov (United States)

    Ehret, U.; Vogelbacher, A.; Moritz, K.; Laurent, S.; Meyer, I.; Haag, I.

    2009-04-01

    In Bavaria, operational flood forecasting has been established since the disastrous flood of 1999. Nowadays, forecasts based on rainfall information from about 700 raingauges and 600 rivergauges are calculated and issued for nearly 100 rivergauges. With the added experience of the 2002 and 2005 floods, awareness grew that the standard deterministic forecast, neglecting the uncertainty associated with each forecast is misleading, creating a false feeling of unambiguousness. As a consequence, a system to identify, quantify and communicate the sources and magnitude of forecast uncertainty has been developed, which will be presented in part I of this study. In this system, the use of ensemble meteorological forecasts plays a key role which will be presented in part II. Developing the system, several constraints stemming from the range of hydrological regimes and operational requirements had to be met: Firstly, operational time constraints obviate the variation of all components of the modeling chain as would be done in a full Monte Carlo simulation. Therefore, an approach was chosen where only the most relevant sources of uncertainty were dynamically considered while the others were jointly accounted for by static error distributions from offline analysis. Secondly, the dominant sources of uncertainty vary over the wide range of forecasted catchments: In alpine headwater catchments, typically of a few hundred square kilometers in size, rainfall forecast uncertainty is the key factor for forecast uncertainty, with a magnitude dynamically changing with the prevailing predictability of the atmosphere. In lowland catchments encompassing several thousands of square kilometers, forecast uncertainty in the desired range (usually up to two days) is mainly dependent on upstream gauge observation quality, routing and unpredictable human impact such as reservoir operation. The determination of forecast uncertainty comprised the following steps: a) From comparison of gauge

  4. Short-term wind power combined forecasting based on error forecast correction

    International Nuclear Information System (INIS)

    Liang, Zhengtang; Liang, Jun; Wang, Chengfu; Dong, Xiaoming; Miao, Xiaofeng

    2016-01-01

    Highlights: • The correlation relationships of short-term wind power forecast errors are studied. • The correlation analysis method of the multi-step forecast errors is proposed. • A strategy selecting the input variables for the error forecast models is proposed. • Several novel combined models based on error forecast correction are proposed. • The combined models have improved the short-term wind power forecasting accuracy. - Abstract: With the increasing contribution of wind power to electric power grids, accurate forecasting of short-term wind power has become particularly valuable for wind farm operators, utility operators and customers. The aim of this study is to investigate the interdependence structure of errors in short-term wind power forecasting that is crucial for building error forecast models with regression learning algorithms to correct predictions and improve final forecasting accuracy. In this paper, several novel short-term wind power combined forecasting models based on error forecast correction are proposed in the one-step ahead, continuous and discontinuous multi-step ahead forecasting modes. First, the correlation relationships of forecast errors of the autoregressive model, the persistence method and the support vector machine model in various forecasting modes have been investigated to determine whether the error forecast models can be established by regression learning algorithms. Second, according to the results of the correlation analysis, the range of input variables is defined and an efficient strategy for selecting the input variables for the error forecast models is proposed. Finally, several combined forecasting models are proposed, in which the error forecast models are based on support vector machine/extreme learning machine, and correct the short-term wind power forecast values. The data collected from a wind farm in Hebei Province, China, are selected as a case study to demonstrate the effectiveness of the proposed

  5. Ion exchange technology assessment report

    International Nuclear Information System (INIS)

    Duhn, E.F.

    1992-01-01

    In the execution of its charter, the SRS Ion Exchange Technology Assessment Team has determined that ion exchange (IX) technology has evolved to the point where it should now be considered as a viable alternative to the SRS reference ITP/LW/PH process. The ion exchange media available today offer the ability to design ion exchange processing systems tailored to the unique physical and chemical properties of SRS soluble HLW's. The technical assessment of IX technology and its applicability to the processing of SRS soluble HLW has demonstrated that IX is unquestionably a viable technology. A task team was chartered to evaluate the technology of ion exchange and its potential for replacing the present In-Tank Precipitation and proposed Late Wash processes to remove Cs, Sr, and Pu from soluble salt solutions at the Savannah River Site. This report documents the ion exchange technology assessment and conclusions of the task team

  6. A Preliminary Study of Grade Forecasting by Students

    Science.gov (United States)

    Armstrong, Michael J.

    2013-01-01

    This experiment enabled undergraduate business students to better assess their progress in a course by quantitatively forecasting their own end-of-course grades. This innovation provided them with predictive feedback in addition to the outcome feedback they were already receiving. A total of 144 students forecast their grades using an…

  7. Forecasting volatility of crude oil markets

    International Nuclear Information System (INIS)

    Kang, Sang Hoon; Kang, Sang-Mok; Yoon, Seong-Min

    2009-01-01

    This article investigates the efficacy of a volatility model for three crude oil markets - Brent, Dubai, and West Texas Intermediate (WTI) - with regard to its ability to forecast and identify volatility stylized facts, in particular volatility persistence or long memory. In this context, we assess persistence in the volatility of the three crude oil prices using conditional volatility models. The CGARCH and FIGARCH models are better equipped to capture persistence than are the GARCH and IGARCH models. The CGARCH and FIGARCH models also provide superior performance in out-of-sample volatility forecasts. We conclude that the CGARCH and FIGARCH models are useful for modeling and forecasting persistence in the volatility of crude oil prices. (author)

  8. Forecasting volatility of crude oil markets

    Energy Technology Data Exchange (ETDEWEB)

    Kang, Sang Hoon [Department of Business Administration, Gyeongsang National University, Jinju, 660-701 (Korea); Kang, Sang-Mok; Yoon, Seong-Min [Department of Economics, Pusan National University, Busan, 609-735 (Korea)

    2009-01-15

    This article investigates the efficacy of a volatility model for three crude oil markets - Brent, Dubai, and West Texas Intermediate (WTI) - with regard to its ability to forecast and identify volatility stylized facts, in particular volatility persistence or long memory. In this context, we assess persistence in the volatility of the three crude oil prices using conditional volatility models. The CGARCH and FIGARCH models are better equipped to capture persistence than are the GARCH and IGARCH models. The CGARCH and FIGARCH models also provide superior performance in out-of-sample volatility forecasts. We conclude that the CGARCH and FIGARCH models are useful for modeling and forecasting persistence in the volatility of crude oil prices. (author)

  9. Petascale Diagnostic Assessment of the Global Portfolio Rainfall Space Missions' Ability to Support Flood Forecasting

    Science.gov (United States)

    Reed, P. M.; Chaney, N.; Herman, J. D.; Wood, E. F.; Ferringer, M. P.

    2015-12-01

    This research represents a multi-institutional collaboration between Cornell University, The Aerospace Corporation, and Princeton University that has completed a Petascale diagnostic assessment of the current 10 satellite missions providing rainfall observations. Our diagnostic assessment has required four core tasks: (1) formally linking high-resolution astrodynamics design and coordination of space assets with their global hydrological impacts within a Petascale "many-objective" global optimization framework, (2) developing a baseline diagnostic evaluation of a 1-degree resolution global implementation of the Variable Infiltration Capacity (VIC) model to establish the required satellite observation frequencies and coverage to maintain acceptable global flood forecasts, (3) evaluating the limitations and vulnerabilities of the full suite of current satellite precipitation missions including the recently approved Global Precipitation Measurement (GPM) mission, and (4) conceptualizing the next generation spaced-based platforms for water cycle observation. Our team exploited over 100 Million hours of computing access on the 700,000+ core Blue Waters machine to radically advance our ability to discover and visualize key system tradeoffs and sensitivities. This project represents to our knowledge the first attempt to develop a 10,000 member Monte Carlo global hydrologic simulation at one degree resolution that characterizes the uncertain effects of changing the available frequencies of satellite precipitation on drought and flood forecasts. The simulation—optimization components of the work have set a theoretical baseline for the best possible frequencies and coverages for global precipitation given unlimited investment, broad international coordination in reconfiguring existing assets, and new satellite constellation design objectives informed directly by key global hydrologic forecasting requirements. Our research poses a step towards realizing the integrated

  10. The Use of Ambient Humidity Conditions to Improve Influenza Forecast

    Science.gov (United States)

    Shaman, J. L.; Kandula, S.; Yang, W.; Karspeck, A. R.

    2017-12-01

    Laboratory and epidemiological evidence indicate that ambient humidity modulates the survival and transmission of influenza. Here we explore whether the inclusion of humidity forcing in mathematical models describing influenza transmission improves the accuracy of forecasts generated with those models. We generate retrospective forecasts for 95 cities over 10 seasons in the United States and assess both forecast accuracy and error. Overall, we find that humidity forcing improves forecast performance and that forecasts generated using daily climatological humidity forcing generally outperform forecasts that utilize daily observed humidity forcing. These findings hold for predictions of outbreak peak intensity, peak timing, and incidence over 2- and 4-week horizons. The results indicate that use of climatological humidity forcing is warranted for current operational influenza forecast and provide further evidence that humidity modulates rates of influenza transmission.

  11. Flash flood forecasting, warning and risk management: the HYDRATE project

    International Nuclear Information System (INIS)

    Borga, M.; Anagnostou, E.N.; Bloeschl, G.; Creutin, J.-D.

    2011-01-01

    Highlights: → We characterize flash flood events in various regions of Europe. → We provide guidance to improve observations and monitoring of flash floods. → Flash floods are associated to orography and are influenced by initial soil moisture conditions. → Models for flash flood forecasting and flash flood hazard assessment are illustrated and discussed. → We examine implications for flood risk policy and discuss recommendations received from end users. - Abstract: The management of flash flood hazards and risks is a critical component of public safety and quality of life. Flash-floods develop at space and time scales that conventional observation systems are not able to monitor for rainfall and river discharge. Consequently, the atmospheric and hydrological generating mechanisms of flash-floods are poorly understood, leading to highly uncertain forecasts of these events. The objective of the HYDRATE project has been to improve the scientific basis of flash flood forecasting by advancing and harmonising a European-wide innovative flash flood observation strategy and developing a coherent set of technologies and tools for effective early warning systems. To this end, the project included actions on the organization of the existing flash flood data patrimony across Europe. The final aim of HYDRATE was to enhance the capability of flash flood forecasting in ungauged basins by exploiting the extended availability of flash flood data and the improved process understanding. This paper provides a review of the work conducted in HYDRATE with a special emphasis on how this body of research can contribute to guide the policy-life cycle concerning flash flood risk management.

  12. Flood Forecasting Based on TIGGE Precipitation Ensemble Forecast

    Directory of Open Access Journals (Sweden)

    Jinyin Ye

    2016-01-01

    Full Text Available TIGGE (THORPEX International Grand Global Ensemble was a major part of the THORPEX (Observing System Research and Predictability Experiment. It integrates ensemble precipitation products from all the major forecast centers in the world and provides systematic evaluation on the multimodel ensemble prediction system. Development of meteorologic-hydrologic coupled flood forecasting model and early warning model based on the TIGGE precipitation ensemble forecast can provide flood probability forecast, extend the lead time of the flood forecast, and gain more time for decision-makers to make the right decision. In this study, precipitation ensemble forecast products from ECMWF, NCEP, and CMA are used to drive distributed hydrologic model TOPX. We focus on Yi River catchment and aim to build a flood forecast and early warning system. The results show that the meteorologic-hydrologic coupled model can satisfactorily predict the flow-process of four flood events. The predicted occurrence time of peak discharges is close to the observations. However, the magnitude of the peak discharges is significantly different due to various performances of the ensemble prediction systems. The coupled forecasting model can accurately predict occurrence of the peak time and the corresponding risk probability of peak discharge based on the probability distribution of peak time and flood warning, which can provide users a strong theoretical foundation and valuable information as a promising new approach.

  13. EU pharmaceutical expenditure forecast.

    Science.gov (United States)

    Urbinati, Duccio; Rémuzat, Cécile; Kornfeld, Åsa; Vataire, Anne-Lise; Cetinsoy, Laurent; Aballéa, Samuel; Mzoughi, Olfa; Toumi, Mondher

    2014-01-01

    With constant incentives for healthcare payers to contain their pharmaceutical budgets, forecasting has become critically important. Some countries have, for instance, developed pharmaceutical horizon scanning units. The objective of this project was to build a model to assess the net effect of the entrance of new patented medicinal products versus medicinal products going off-patent, with a defined forecast horizon, on selected European Union (EU) Member States' pharmaceutical budgets. This model took into account population ageing, as well as current and future country-specific pricing, reimbursement, and market access policies (the project was performed for the European Commission; see http://ec.europa.eu/health/healthcare/key_documents/index_en.htm). In order to have a representative heterogeneity of EU Member States, the following countries were selected for the analysis: France, Germany, Greece, Hungary, Poland, Portugal, and the United Kingdom. A forecasting period of 5 years (2012-2016) was chosen to assess the net pharmaceutical budget impact. A model for generics and biosimilars was developed for each country. The model estimated a separate and combined effect of the direct and indirect impacts of the patent cliff. A second model, estimating the sales development and the risk of development failure, was developed for new drugs. New drugs were reviewed individually to assess their clinical potential and translate it into commercial potential. The forecast was carried out according to three perspectives (healthcare public payer, society, and manufacturer), and several types of distribution chains (retail, hospital, and combined retail and hospital). Probabilistic and deterministic sensitivity analyses were carried out. According to the model, all countries experienced drug budget reductions except Poland (+€41 million). Savings were expected to be the highest in the United Kingdom (-€9,367 million), France (-€5,589 million), and, far behind them

  14. Logical design of a decision support system to forecast technology, prices and costs for the national communications system

    Science.gov (United States)

    Williams, K. A.; Partridge, E. C., III

    1984-09-01

    Originally envisioned as a means to integrate the many systems found throughout the government, the general mission of the NCS continues to be to ensure the survivability of communications during and subsequent to any national emergency. In order to accomplish this mission the NCS is an arrangement of heterogeneous telecommunications systems which are provided by their sponsor Federal agencies. The physical components of Federal telecommunications systems and networks include telephone and digital data switching facilities and primary common user communications centers; Special purpose local delivery message switching and exchange facilities; Government owned or leased radio systems; Technical control facilities which are under exclusive control of a government agency. This thesis describes the logical design of a proposed decision support system for use by the National Communications System in forecasting technology, prices, and costs. It is general in nature and only includes those forecasting models which are suitable for computer implementation. Because it is a logical design it can be coded and applied in many different hardware and/or software configurations.

  15. ASSESSMENT OF GALLIUM OXIDE TECHNOLOGY

    Science.gov (United States)

    2017-08-01

    AFRL-RY-WP-TR-2017-0167 ASSESSMENT OF GALLIUM OXIDE TECHNOLOGY Burhan Bayraktaroglu Devices for Sensing Branch Aerospace...TITLE AND SUBTITLE ASSESSMENT OF GALLIUM OXIDE TECHNOLOGY 5a. CONTRACT NUMBER In-house 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER N/A 6...report summarizes the current status of the Ga2O3 technology based on published results on theoretical electronic structure, materials growth, and

  16. Forecasting Housing Approvals in Australia: Do Forecasters Herd?

    DEFF Research Database (Denmark)

    Stadtmann, Georg; Pierdzioch; Rülke

    2012-01-01

    Price trends in housing markets may reflect herding of market participants. A natural question is whether such herding, to the extent that it occurred, reflects herding in forecasts of professional forecasters. Using more than 6,000 forecasts of housing approvals for Australia, we did not find...

  17. The use of ambient humidity conditions to improve influenza forecast.

    Science.gov (United States)

    Shaman, Jeffrey; Kandula, Sasikiran; Yang, Wan; Karspeck, Alicia

    2017-11-01

    Laboratory and epidemiological evidence indicate that ambient humidity modulates the survival and transmission of influenza. Here we explore whether the inclusion of humidity forcing in mathematical models describing influenza transmission improves the accuracy of forecasts generated with those models. We generate retrospective forecasts for 95 cities over 10 seasons in the United States and assess both forecast accuracy and error. Overall, we find that humidity forcing improves forecast performance (at 1-4 lead weeks, 3.8% more peak week and 4.4% more peak intensity forecasts are accurate than with no forcing) and that forecasts generated using daily climatological humidity forcing generally outperform forecasts that utilize daily observed humidity forcing (4.4% and 2.6% respectively). These findings hold for predictions of outbreak peak intensity, peak timing, and incidence over 2- and 4-week horizons. The results indicate that use of climatological humidity forcing is warranted for current operational influenza forecast.

  18. Evaluating the performance of infectious disease forecasts: A comparison of climate-driven and seasonal dengue forecasts for Mexico

    OpenAIRE

    Johansson, Michael A.; Reich, Nicholas G.; Hota, Aditi; Brownstein, John S.; Santillana, Mauricio

    2016-01-01

    Dengue viruses, which infect millions of people per year worldwide, cause large epidemics that strain healthcare systems. Despite diverse efforts to develop forecasting tools including autoregressive time series, climate-driven statistical, and mechanistic biological models, little work has been done to understand the contribution of different components to improved prediction. We developed a framework to assess and compare dengue forecasts produced from different types of models and evaluate...

  19. Assessing for Technological Literacy

    Science.gov (United States)

    Engstrom, Daniel E.

    2004-01-01

    Designing standards-based assessment is a key component of a quality technology education program. For students to become technologically literate, it is important that the teacher understands how to measure student understandings and abilities in the study of technology. This article is written to help teachers and teacher educators recognize the…

  20. A Conceptual Methodology for Assessing Acquisition Requirements Robustness against Technology Uncertainties

    Science.gov (United States)

    Chou, Shuo-Ju

    2011-12-01

    -makers with the ability to assess or measure the robustness of program requirements against such uncertainties. A literature review of techniques for forecasting technology performance and development uncertainties and subsequent impacts on capability, budget, and schedule requirements resulted in the conclusion that an analysis process that coupled a probabilistic analysis technique such as Monte Carlo Simulations with quantitative and parametric models of technology performance impact and technology development time and cost requirements would allow the probabilities of meeting specific constraints of these requirements to be established. These probabilities of requirements success metrics can then be used as a quantitative and probabilistic measure of program requirements robustness against technology uncertainties. Combined with a Multi-Objective Genetic Algorithm optimization process and computer-based Decision Support System, critical information regarding requirements robustness against technology uncertainties can be captured and quantified for acquisition decision-makers. This results in a more informed and justifiable selection of program technologies during initial program definition as well as formulation of program development and risk management strategies. To meet the stated research objective, the ENhanced TEchnology Robustness Prediction and RISk Evaluation (ENTERPRISE) methodology was formulated to provide a structured and transparent process for integrating these enabling techniques to provide a probabilistic and quantitative assessment of acquisition program requirements robustness against technology performance and development uncertainties. In order to demonstrate the capabilities of the ENTERPRISE method and test the research Hypotheses, an demonstration application of this method was performed on a notional program for acquiring the Carrier-based Suppression of Enemy Air Defenses (SEAD) using Unmanned Combat Aircraft Systems (UCAS) and their enabling

  1. Outlook for renewable energy technologies: Assessment of international programs and policies

    Energy Technology Data Exchange (ETDEWEB)

    Branstetter, L.J.; Vidal, R.C.; Bruch, V.L.; Zurn, R.

    1995-02-01

    The report presents an evaluation of worldwide research efforts in three specific renewable energy technologies, with a view towards future United States (US) energy security, environmental factors, and industrial competitiveness. The overall energy technology priorities of foreign governments and industry leaders, as well as the motivating factors for these priorities, are identified and evaluated from both technological and policy perspectives. The specific technologies of interest are wind, solar thermal, and solar photovoltaics (PV). These program areas, as well as the overall energy policies of Denmark, France, Germany, Italy, the United Kingdom (UK), Japan, Russia, and the European Community as a whole are described. The present and likely future picture for worldwide technological leadership in these technologies-is portrayed. The report is meant to help in forecasting challenges to US preeminence in the various technology areas, particularly over the next ten years, and to help guide US policy-makers as they try to identify specific actions which would help to retain and/or expand the US leadership position.

  2. A nowcast-forecast information system for PWS

    International Nuclear Information System (INIS)

    Thomas, G.L.; Cox, W.

    2000-01-01

    The development of the Prince William Sound Oil Spill Recovery Institute's (ORI) nowcast-forecast information system was discussed. OSRI addresses oil spill response and prevention research and development in the Arctic and subArctic. A realistic electronic model of the ecosystem was a much needed tool for efficient prioritization of oil spill technologies. The OSRI Sound Ecosystem Assessment (SEA) research program focused on developing a physical-biological model that consisted of static and biological resources that change over long time periods. This includes bathymetry, shoreline type, and substrate-dependent vegetation. It also focused on developing a model of dynamic properties such as wind, weather, plankton, and wildlife populations that undergo significant changes on annual or shorter time scales. The nowcast information system is a long-term development project which uses the Princeton ocean model (POM), a static runoff model, a network of weather and water observation stations, an Intranet which allows the observational data to run in near-real time and an Internet home page. It will contribute to sustaining the natural resources of coastal areas. It was concluded that the nowcast-forecast information system has short-term applications to oil spill prevention and response and long-term applications to the natural resources at risk to spills. 33 refs

  3. Robust forecast comparison

    OpenAIRE

    Jin, Sainan; Corradi, Valentina; Swanson, Norman

    2015-01-01

    Forecast accuracy is typically measured in terms of a given loss function. However, as a consequence of the use of misspecified models in multiple model comparisons, relative forecast rankings are loss function dependent. This paper addresses this issue by using a novel criterion for forecast evaluation which is based on the entire distribution of forecast errors. We introduce the concepts of general-loss (GL) forecast superiority and convex-loss (CL) forecast superiority, and we establish a ...

  4. Advances in electric power and energy systems load and price forecasting

    CERN Document Server

    2017-01-01

    A comprehensive review of state-of-the-art approaches to power systems forecasting from the most respected names in the field, internationally. Advances in Electric Power and Energy Systems is the first book devoted exclusively to a subject of increasing urgency to power systems planning and operations. Written for practicing engineers, researchers, and post-grads concerned with power systems planning and forecasting, this book brings together contributions from many of the world’s foremost names in the field who address a range of critical issues, from forecasting power system load to power system pricing to post-storm service restoration times, river flow forecasting, and more. In a time of ever-increasing energy demands, mounting concerns over the environmental impacts of power generation, and the emergence of new, smart-grid technologies, electricity price forecasting has assumed a prominent role within both the academic and industrial ar nas. Short-run forecasting of electricity prices has become nece...

  5. An economic framework for forecasting land-use and ecosystem change

    International Nuclear Information System (INIS)

    Lewis, David J.

    2010-01-01

    This paper develops a joint econometric-simulation framework to forecast detailed empirical distributions of the spatial pattern of land-use and ecosystem change. In-sample and out-of-sample forecasting tests are used to examine the performance of the parcel-scale econometric and simulation models, and the importance of multiple forecasting challenges is assessed. The econometric-simulation method is integrated with an ecological model to generate forecasts of the probability of localized extinctions of an amphibian species. The paper demonstrates the potential of integrating economic and ecological models to generate ecological forecasts in the presence of alternative market conditions and land-use policy constraints. (author)

  6. Assessing nano cellulose developments using science and technology indicators

    International Nuclear Information System (INIS)

    Milanez, Douglas Henrique; Amaral, Roniberto Morato do; Faria, Leandro Innocentini Lopes de; Gregolin, Jose Angelo Rodrigues

    2013-01-01

    This research aims to examine scientific and technological trends of developments in nano cellulose based on scientometric and patent indicators obtained from the Science Citation Index and Derwent Innovations Index in 2001-2010. The overall nano cellulose activity indicators were compared to nanotechnology and other selected nano materials. Scientific and technological future developments in nano cellulose were forecasted using extrapolation growth curves and the main countries were also mapped. The results showed that nano cellulose publications and patent documents have increased rapidly over the last five years with an average growth rate higher than that of nanotechnology and fullerene. The USA, Japan, France, Sweden and Finland all played a significant role in nano cellulose development and the extrapolation growth curves suggested that nano cellulose scientific and technological activities are still emerging. Finally, the evidence from this study recommends monitoring nano cellulose S and T advances in the coming years. (author)

  7. Assessing nano cellulose developments using science and technology indicators

    Energy Technology Data Exchange (ETDEWEB)

    Milanez, Douglas Henrique; Amaral, Roniberto Morato do; Faria, Leandro Innocentini Lopes de; Gregolin, Jose Angelo Rodrigues, E-mail: douglasmilanez@yahoo.com.br [Universidade Federal de Sao Carlos (UFSCar), SP (Brazil). Nucleo de Informacao Tecnologica em Materiais. Dept. de Engenharia de Materiais

    2013-11-01

    This research aims to examine scientific and technological trends of developments in nano cellulose based on scientometric and patent indicators obtained from the Science Citation Index and Derwent Innovations Index in 2001-2010. The overall nano cellulose activity indicators were compared to nanotechnology and other selected nano materials. Scientific and technological future developments in nano cellulose were forecasted using extrapolation growth curves and the main countries were also mapped. The results showed that nano cellulose publications and patent documents have increased rapidly over the last five years with an average growth rate higher than that of nanotechnology and fullerene. The USA, Japan, France, Sweden and Finland all played a significant role in nano cellulose development and the extrapolation growth curves suggested that nano cellulose scientific and technological activities are still emerging. Finally, the evidence from this study recommends monitoring nano cellulose S and T advances in the coming years. (author)

  8. A hybrid approach for probabilistic forecasting of electricity price

    DEFF Research Database (Denmark)

    Wan, Can; Xu, Zhao; Wang, Yelei

    2014-01-01

    to the nonstationarities involved in market clearing prices (MCPs), it is rather difficult to accurately predict MCPs in advance. The challenge is getting intensified as more and more renewable energy and other new technologies emerged in smart grids. Therefore transformation from traditional point forecasts...... electricity price forecasting is proposed in this paper. The effectiveness of the proposed hybrid method has been validated through comprehensive tests using real price data from Australian electricity market.......The electricity market plays a key role in realizing the economic prophecy of smart grids. Accurate and reliable electricity market price forecasting is essential to facilitate various decision making activities of market participants in the future smart grid environment. However, due...

  9. A High Precision Artificial Neural Networks Model for Short-Term Energy Load Forecasting

    Directory of Open Access Journals (Sweden)

    Ping-Huan Kuo

    2018-01-01

    Full Text Available One of the most important research topics in smart grid technology is load forecasting, because accuracy of load forecasting highly influences reliability of the smart grid systems. In the past, load forecasting was obtained by traditional analysis techniques such as time series analysis and linear regression. Since the load forecast focuses on aggregated electricity consumption patterns, researchers have recently integrated deep learning approaches with machine learning techniques. In this study, an accurate deep neural network algorithm for short-term load forecasting (STLF is introduced. The forecasting performance of proposed algorithm is compared with performances of five artificial intelligence algorithms that are commonly used in load forecasting. The Mean Absolute Percentage Error (MAPE and Cumulative Variation of Root Mean Square Error (CV-RMSE are used as accuracy evaluation indexes. The experiment results show that MAPE and CV-RMSE of proposed algorithm are 9.77% and 11.66%, respectively, displaying very high forecasting accuracy.

  10. The use of ambient humidity conditions to improve influenza forecast.

    Directory of Open Access Journals (Sweden)

    Jeffrey Shaman

    2017-11-01

    Full Text Available Laboratory and epidemiological evidence indicate that ambient humidity modulates the survival and transmission of influenza. Here we explore whether the inclusion of humidity forcing in mathematical models describing influenza transmission improves the accuracy of forecasts generated with those models. We generate retrospective forecasts for 95 cities over 10 seasons in the United States and assess both forecast accuracy and error. Overall, we find that humidity forcing improves forecast performance (at 1-4 lead weeks, 3.8% more peak week and 4.4% more peak intensity forecasts are accurate than with no forcing and that forecasts generated using daily climatological humidity forcing generally outperform forecasts that utilize daily observed humidity forcing (4.4% and 2.6% respectively. These findings hold for predictions of outbreak peak intensity, peak timing, and incidence over 2- and 4-week horizons. The results indicate that use of climatological humidity forcing is warranted for current operational influenza forecast.

  11. SUSTAINABILITY LOGISTICS BASING SCIENCE AND TECHNOLOGY OBJECTIVE DEMONSTRATION; SELECTED TECHNOLOGY ASSESSMENT

    Science.gov (United States)

    2018-03-22

    BASING SCIENCE AND TECHNOLOGY OBJECTIVE – DEMONSTRATION; SELECTED TECHNOLOGY ASSESSMENT by Gregg J. Gildea Paul D. Carpenter Benjamin J...Campbell William F. Harris* Michael A. McCluskey** and José A. Miletti*** *General Dynamics Information Technology Fairfax, VA 22030 **Maneuver...SCIENCE AND TECHNOLOGY OBJECTIVE – DEMONSTRATION; SELECTED TECHNOLOGY ASSESSMENT 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT

  12. On the effect of model parameters on forecast objects

    Science.gov (United States)

    Marzban, Caren; Jones, Corinne; Li, Ning; Sandgathe, Scott

    2018-04-01

    Many physics-based numerical models produce a gridded, spatial field of forecasts, e.g., a temperature map. The field for some quantities generally consists of spatially coherent and disconnected objects. Such objects arise in many problems, including precipitation forecasts in atmospheric models, eddy currents in ocean models, and models of forest fires. Certain features of these objects (e.g., location, size, intensity, and shape) are generally of interest. Here, a methodology is developed for assessing the impact of model parameters on the features of forecast objects. The main ingredients of the methodology include the use of (1) Latin hypercube sampling for varying the values of the model parameters, (2) statistical clustering algorithms for identifying objects, (3) multivariate multiple regression for assessing the impact of multiple model parameters on the distribution (across the forecast domain) of object features, and (4) methods for reducing the number of hypothesis tests and controlling the resulting errors. The final output of the methodology is a series of box plots and confidence intervals that visually display the sensitivities. The methodology is demonstrated on precipitation forecasts from a mesoscale numerical weather prediction model.

  13. Ex-post evaluations of demand forecast accuracy

    DEFF Research Database (Denmark)

    Nicolaisen, Morten Skou; Driscoll, Patrick Arthur

    2014-01-01

    Travel demand forecasts play a crucial role in the preparation of decision support to policy makers in the field of transport planning. The results feed directly into impact appraisals such as cost benefit analyses and environmental impact assessments, which are mandatory for large public works...... projects in many countries. Over the last couple of decades there has been an increasing attention to the lack of demand forecast accuracy, but since data availability for comprehensive ex- post appraisals is problematic, such studies are still relatively rare. The present paper presents a review...... of the largest ex-post studies of demand forecast accuracy for transport infrastructure projects. The focus is twofold; to provide an overview of observed levels of demand forecast inaccuracy and to explore the primary explanations offered for the observed inaccuracy. Inaccuracy in the form of both bias...

  14. Forecasting Skill

    Science.gov (United States)

    1981-01-01

    for the third and fourth day precipitation forecasts. A marked improvement was shown for the consensus 24 hour precipitation forecast, and small... Zuckerberg (1980) found a small long term skill increase in forecasts of heavy snow events for nine eastern cities. Other National Weather Service...and maximum temperature) are each awarded marks 2, 1, or 0 according to whether the forecast is correct, 8 - *- -**■*- ———"—- - -■ t0m 1 MM—IB I

  15. Complex relationship between seasonal streamflow forecast skill and value in reservoir operations

    Directory of Open Access Journals (Sweden)

    S. W. D. Turner

    2017-09-01

    Full Text Available Considerable research effort has recently been directed at improving and operationalising ensemble seasonal streamflow forecasts. Whilst this creates new opportunities for improving the performance of water resources systems, there may also be associated risks. Here, we explore these potential risks by examining the sensitivity of forecast value (improvement in system performance brought about by adopting forecasts to changes in the forecast skill for a range of hypothetical reservoir designs with contrasting operating objectives. Forecast-informed operations are simulated using rolling horizon, adaptive control and then benchmarked against optimised control rules to assess performance improvements. Results show that there exists a strong relationship between forecast skill and value for systems operated to maintain a target water level. But this relationship breaks down when the reservoir is operated to satisfy a target demand for water; good forecast accuracy does not necessarily translate into performance improvement. We show that the primary cause of this behaviour is the buffering role played by storage in water supply reservoirs, which renders the forecast superfluous for long periods of the operation. System performance depends primarily on forecast accuracy when critical decisions are made – namely during severe drought. As it is not possible to know in advance if a forecast will perform well at such moments, we advocate measuring the consistency of forecast performance, through bootstrap resampling, to indicate potential usefulness in storage operations. Our results highlight the need for sensitivity assessment in value-of-forecast studies involving reservoirs with supply objectives.

  16. Identifying and Assessing Life-Cycle-Related Critical Technology Elements (CTEs) for Technology Readiness Assessments (TRAs)

    National Research Council Canada - National Science Library

    Mandelbaum, Jay

    2006-01-01

    .... Because these technologies are not emphasized in the current Technology Readiness Assessment (TRA) process this document is intended to improve the focus on life-cycle-related technologies in TRAs...

  17. Sub-Ensemble Coastal Flood Forecasting: A Case Study of Hurricane Sandy

    Directory of Open Access Journals (Sweden)

    Justin A. Schulte

    2017-12-01

    Full Text Available In this paper, it is proposed that coastal flood ensemble forecasts be partitioned into sub-ensemble forecasts using cluster analysis in order to produce representative statistics and to measure forecast uncertainty arising from the presence of clusters. After clustering the ensemble members, the ability to predict the cluster into which the observation will fall can be measured using a cluster skill score. Additional sub-ensemble and composite skill scores are proposed for assessing the forecast skill of a clustered ensemble forecast. A recently proposed method for statistically increasing the number of ensemble members is used to improve sub-ensemble probabilistic estimates. Through the application of the proposed methodology to Sandy coastal flood reforecasts, it is demonstrated that statistics computed using only ensemble members belonging to a specific cluster are more representative than those computed using all ensemble members simultaneously. A cluster skill-cluster uncertainty index relationship is identified, which is the cluster analog of the documented spread-skill relationship. Two sub-ensemble skill scores are shown to be positively correlated with cluster forecast skill, suggesting that skillfully forecasting the cluster into which the observation will fall is important to overall forecast skill. The identified relationships also suggest that the number of ensemble members within in each cluster can be used as guidance for assessing the potential for forecast error. The inevitable existence of ensemble member clusters in tidally dominated total water level prediction systems suggests that clustering is a necessary post-processing step for producing representative and skillful total water level forecasts.

  18. Evaluating information in multiple horizon forecasts. The DOE's energy price forecasts

    International Nuclear Information System (INIS)

    Sanders, Dwight R.; Manfredo, Mark R.; Boris, Keith

    2009-01-01

    The United States Department of Energy's (DOE) quarterly price forecasts for energy commodities are examined to determine the incremental information provided at the one-through four-quarter forecast horizons. A direct test for determining information content at alternative forecast horizons, developed by Vuchelen and Gutierrez [Vuchelen, J. and Gutierrez, M.-I. 'A Direct Test of the Information Content of the OECD Growth Forecasts.' International Journal of Forecasting. 21(2005):103-117.], is used. The results suggest that the DOE's price forecasts for crude oil, gasoline, and diesel fuel do indeed provide incremental information out to three-quarters ahead, while natural gas and electricity forecasts are informative out to the four-quarter horizon. In contrast, the DOE's coal price forecasts at two-, three-, and four-quarters ahead provide no incremental information beyond that provided for the one-quarter horizon. Recommendations of how to use these results for making forecast adjustments is also provided. (author)

  19. Market penetration of new energy technologies

    Energy Technology Data Exchange (ETDEWEB)

    Packey, D.J.

    1993-02-01

    This report examines the characteristics, advantages, disadvantages, and, for some, the mathematical formulas of forecasting methods that can be used to forecast the market penetration of renewable energy technologies. Among the methods studied are subjective estimation, market surveys, historical analogy models, cost models, diffusion models, time-series models, and econometric models. Some of these forecasting methods are more effective than others at different developmental stages of new technologies.

  20. History of the international societies in health technology assessment: International Society for Technology Assessment in Health Care and Health Technology Assessment International.

    Science.gov (United States)

    Banta, David; Jonsson, Egon; Childs, Paul

    2009-07-01

    The International Society for Technology Assessment in Health Care (ISTAHC) was formed in 1985. It grew out of the increasing awareness of the international dimensions of health technology assessment (HTA) and the need for new communication methods at the international level. The main function of ISTAHC was to present an annual conference, which gradually grew in size, and also to generally improve in quality from to year. ISTAHC overextended itself financially early in the first decade of the 2000s and had to cease its existence. A new society, Health Technology Assessment international (HTAi), based on many of the same ideas and people, grew up beginning in the year 2003. The two societies have played a large role in making the field of HTA visible to people around the world and providing a forum for discussion on the methods and role of HTA.

  1. Solar Resource Assessment with Sky Imagery and a Virtual Testbed for Sky Imager Solar Forecasting

    Science.gov (United States)

    Kurtz, Benjamin Bernard

    In recent years, ground-based sky imagers have emerged as a promising tool for forecasting solar energy on short time scales (0 to 30 minutes ahead). Following the development of sky imager hardware and algorithms at UC San Diego, we present three new or improved algorithms for sky imager forecasting and forecast evaluation. First, we present an algorithm for measuring irradiance with a sky imager. Sky imager forecasts are often used in conjunction with other instruments for measuring irradiance, so this has the potential to decrease instrumentation costs and logistical complexity. In particular, the forecast algorithm itself often relies on knowledge of the current irradiance which can now be provided directly from the sky images. Irradiance measurements are accurate to within about 10%. Second, we demonstrate a virtual sky imager testbed that can be used for validating and enhancing the forecast algorithm. The testbed uses high-quality (but slow) simulations to produce virtual clouds and sky images. Because virtual cloud locations are known, much more advanced validation procedures are possible with the virtual testbed than with measured data. In this way, we are able to determine that camera geometry and non-uniform evolution of the cloud field are the two largest sources of forecast error. Finally, with the assistance of the virtual sky imager testbed, we develop improvements to the cloud advection model used for forecasting. The new advection schemes are 10-20% better at short time horizons.

  2. Increasing the temporal resolution of direct normal solar irradiance forecasted series

    Science.gov (United States)

    Fernández-Peruchena, Carlos M.; Gastón, Martin; Schroedter-Homscheidt, Marion; Marco, Isabel Martínez; Casado-Rubio, José L.; García-Moya, José Antonio

    2017-06-01

    A detailed knowledge of the solar resource is a critical point in the design and control of Concentrating Solar Power (CSP) plants. In particular, accurate forecasting of solar irradiance is essential for the efficient operation of solar thermal power plants, the management of energy markets, and the widespread implementation of this technology. Numerical weather prediction (NWP) models are commonly used for solar radiation forecasting. In the ECMWF deterministic forecasting system, all forecast parameters are commercially available worldwide at 3-hourly intervals. Unfortunately, as Direct Normal solar Irradiance (DNI) exhibits a great variability due to the dynamic effects of passing clouds, 3-h time resolution is insufficient for accurate simulations of CSP plants due to their nonlinear response to DNI, governed by various thermal inertias due to their complex response characteristics. DNI series of hourly or sub-hourly frequency resolution are normally used for an accurate modeling and analysis of transient processes in CSP technologies. In this context, the objective of this study is to propose a methodology for generating synthetic DNI time series at 1-h (or higher) temporal resolution from 3-h DNI series. The methodology is based upon patterns as being defined with help of the clear-sky envelope approach together with a forecast of maximum DNI value, and it has been validated with high quality measured DNI data.

  3. A robust method to forecast volcanic ash clouds

    Science.gov (United States)

    Denlinger, Roger P.; Pavolonis, Mike; Sieglaff, Justin

    2012-01-01

    Ash clouds emanating from volcanic eruption columns often form trails of ash extending thousands of kilometers through the Earth's atmosphere, disrupting air traffic and posing a significant hazard to air travel. To mitigate such hazards, the community charged with reducing flight risk must accurately assess risk of ash ingestion for any flight path and provide robust forecasts of volcanic ash dispersal. In response to this need, a number of different transport models have been developed for this purpose and applied to recent eruptions, providing a means to assess uncertainty in forecasts. Here we provide a framework for optimal forecasts and their uncertainties given any model and any observational data. This involves random sampling of the probability distributions of input (source) parameters to a transport model and iteratively running the model with different inputs, each time assessing the predictions that the model makes about ash dispersal by direct comparison with satellite data. The results of these comparisons are embodied in a likelihood function whose maximum corresponds to the minimum misfit between model output and observations. Bayes theorem is then used to determine a normalized posterior probability distribution and from that a forecast of future uncertainty in ash dispersal. The nature of ash clouds in heterogeneous wind fields creates a strong maximum likelihood estimate in which most of the probability is localized to narrow ranges of model source parameters. This property is used here to accelerate probability assessment, producing a method to rapidly generate a prediction of future ash concentrations and their distribution based upon assimilation of satellite data as well as model and data uncertainties. Applying this method to the recent eruption of Eyjafjallajökull in Iceland, we show that the 3 and 6 h forecasts of ash cloud location probability encompassed the location of observed satellite-determined ash cloud loads, providing an

  4. Wind field forecast for accidental release of radiative materials

    International Nuclear Information System (INIS)

    Kang Ling; Chen Jiayi; Cai Xuhui

    2003-01-01

    A meso-scale wind field forecast model was designed for emergency environmental assessment in case of accidental release of radiative materials from a nuclear power station. Actual practice of the model showed that it runs fast, has wind field prediction function, and the result given is accurate. With meteorological data collected from weather stations, and pre-treated by a wind field diagnostic model, the initial wind fields at different times were inputted as initial values and assimilation fields for the forecasting model. The model, in turn, worked out to forecast meso-scale wind field of 24 hours in a horizontal domain of 205 km x 205 km. And then, the diagnostic model was employed again with the forecasting data to obtain more detail information of disturbed wind field by local terrain in a smaller domain of 20.5 km x 20.5 km, of which the nuclear power station is at the center. Using observation data in January, April, July and October of 1996 over the area of Hangzhou Bay, wind fields in these 4 months were simulated by different assimilation time and number of the weather stations for a sensitive test. Results indicated that the method used here has increased accuracy of the forecasted wind fields. And incorporating diagnostic method with the wind field forecast model has greatly increased efficiency of the wind field forecast for the smaller domain. This model and scheme have been used in Environmental Consequence Assessment System of Nuclear Accident in Qinshan Area

  5. National Forecast Charts

    Science.gov (United States)

    code. Press enter or select the go button to submit request Local forecast by "City, St" or Prediction Center on Twitter NCEP Quarterly Newsletter WPC Home Analyses and Forecasts National Forecast to all federal, state, and local government web resources and services. National Forecast Charts

  6. Solar Storm GIC Forecasting: Solar Shield Extension Development of the End-User Forecasting System Requirements

    Science.gov (United States)

    Pulkkinen, A.; Mahmood, S.; Ngwira, C.; Balch, C.; Lordan, R.; Fugate, D.; Jacobs, W.; Honkonen, I.

    2015-01-01

    A NASA Goddard Space Flight Center Heliophysics Science Division-led team that includes NOAA Space Weather Prediction Center, the Catholic University of America, Electric Power Research Institute (EPRI), and Electric Research and Management, Inc., recently partnered with the Department of Homeland Security (DHS) Science and Technology Directorate (S&T) to better understand the impact of Geomagnetically Induced Currents (GIC) on the electric power industry. This effort builds on a previous NASA-sponsored Applied Sciences Program for predicting GIC, known as Solar Shield. The focus of the new DHS S&T funded effort is to revise and extend the existing Solar Shield system to enhance its forecasting capability and provide tailored, timely, actionable information for electric utility decision makers. To enhance the forecasting capabilities of the new Solar Shield, a key undertaking is to extend the prediction system coverage across Contiguous United States (CONUS), as the previous version was only applicable to high latitudes. The team also leverages the latest enhancements in space weather modeling capacity residing at Community Coordinated Modeling Center to increase the Technological Readiness Level, or Applications Readiness Level of the system http://www.nasa.gov/sites/default/files/files/ExpandedARLDefinitions4813.pdf.

  7. Short-term Local Forecasting by Artificial Intelligence Techniques and Assess Related Social Effects from Heterogeneous Data

    OpenAIRE

    Gong, Bing

    2017-01-01

    This work aims to use the sophisticated artificial intelligence and statistic techniques to forecast pollution and assess its social impact. To achieve the target of the research, this study is divided into several research sub-objectives as follows: First research sub-objective: propose a framework for relocating and reconfiguring the existing pollution monitoring networks by using feature selection, artificial intelligence techniques, and information theory. Second research sub-objective: c...

  8. Canadian nuclear power plant construction cost forecast and analysis

    International Nuclear Information System (INIS)

    Keng, C.W.K.

    1985-01-01

    Because of the huge volume of capital required to construct a modern electric power generating station, investment decisions have to be made with as complete an understanding of the consequence of the decision as possible. This understanding must be provided by the evaluation of the situation to take place in the future. This paper attempts to use an econometric method to forecast the construction costs escalation of a standard Canadian nuclear generating station (NGS). A review of the history of Canadian nuclear electric power is provided. The major components of the construction costs of a Canadian NGS are studied and summarized. A data base is built and indexes are prepared. Based on these indexes an econometric forecasting model is constructed using an apparently new econometric methodology of forecasting modelling. Forecasts for a period of forty years are generated and applications of alternative scenario forecasts and range forecasts to uncertainty assessment are demonstrated. The indexes, the model, and the forecasts and their applications, to the best of the author's knowledge, are the very first ever done for Canadian NGS constructions

  9. Towards Energy Efficiency: Forecasting Indoor Temperature via Multivariate Analysis

    Directory of Open Access Journals (Sweden)

    Juan Pardo

    2013-09-01

    Full Text Available The small medium large system (SMLsystem is a house built at the Universidad CEU Cardenal Herrera (CEU-UCH for participation in the Solar Decathlon 2013 competition. Several technologies have been integrated to reduce power consumption. One of these is a forecasting system based on artificial neural networks (ANNs, which is able to predict indoor temperature in the near future using captured data by a complex monitoring system as the input. A study of the impact on forecasting performance of different covariate combinations is presented in this paper. Additionally, a comparison of ANNs with the standard statistical forecasting methods is shown. The research in this paper has been focused on forecasting the indoor temperature of a house, as it is directly related to HVAC—heating, ventilation and air conditioning—system consumption. HVAC systems at the SMLsystem house represent 53:89% of the overall power consumption. The energy used to maintain temperature was measured to be 30%–38:9% of the energy needed to lower it. Hence, these forecasting measures allow the house to adapt itself to future temperature conditions by using home automation in an energy-efficient manner. Experimental results show a high forecasting accuracy and therefore, they might be used to efficiently control an HVAC system.

  10. Benefits of seasonal forecasts of crop yields

    Science.gov (United States)

    Sakurai, G.; Okada, M.; Nishimori, M.; Yokozawa, M.

    2017-12-01

    Major factors behind recent fluctuations in food prices include increased biofuel production and oil price fluctuations. In addition, several extreme climate events that reduced worldwide food production coincided with upward spikes in food prices. The stabilization of crop yields is one of the most important tasks to stabilize food prices and thereby enhance food security. Recent development of technologies related to crop modeling and seasonal weather forecasting has made it possible to forecast future crop yields for maize and soybean. However, the effective use of these technologies remains limited. Here we present the potential benefits of seasonal crop-yield forecasts on a global scale for choice of planting day. For this purpose, we used a model (PRYSBI-2) that can well replicate past crop yields both for maize and soybean. This model system uses a Bayesian statistical approach to estimate the parameters of a basic process-based model of crop growth. The spatial variability of model parameters was considered by estimating the posterior distribution of the parameters from historical yield data by using the Markov-chain Monte Carlo (MCMC) method with a resolution of 1.125° × 1.125°. The posterior distributions of model parameters were estimated for each spatial grid with 30 000 MCMC steps of 10 chains each. By using this model and the estimated parameter distributions, we were able to estimate not only crop yield but also levels of associated uncertainty. We found that the global average crop yield increased about 30% as the result of the optimal selection of planting day and that the seasonal forecast of crop yield had a large benefit in and near the eastern part of Brazil and India for maize and the northern area of China for soybean. In these countries, the effects of El Niño and Indian Ocean dipole are large. The results highlight the importance of developing a system to forecast global crop yields.

  11. Improving wave forecasting by integrating ensemble modelling and machine learning

    Science.gov (United States)

    O'Donncha, F.; Zhang, Y.; James, S. C.

    2017-12-01

    Modern smart-grid networks use technologies to instantly relay information on supply and demand to support effective decision making. Integration of renewable-energy resources with these systems demands accurate forecasting of energy production (and demand) capacities. For wave-energy converters, this requires wave-condition forecasting to enable estimates of energy production. Current operational wave forecasting systems exhibit substantial errors with wave-height RMSEs of 40 to 60 cm being typical, which limits the reliability of energy-generation predictions thereby impeding integration with the distribution grid. In this study, we integrate physics-based models with statistical learning aggregation techniques that combine forecasts from multiple, independent models into a single "best-estimate" prediction of the true state. The Simulating Waves Nearshore physics-based model is used to compute wind- and currents-augmented waves in the Monterey Bay area. Ensembles are developed based on multiple simulations perturbing input data (wave characteristics supplied at the model boundaries and winds) to the model. A learning-aggregation technique uses past observations and past model forecasts to calculate a weight for each model. The aggregated forecasts are compared to observation data to quantify the performance of the model ensemble and aggregation techniques. The appropriately weighted ensemble model outperforms an individual ensemble member with regard to forecasting wave conditions.

  12. Improving operational flood forecasting through data assimilation

    Science.gov (United States)

    Rakovec, Oldrich; Weerts, Albrecht; Uijlenhoet, Remko; Hazenberg, Pieter; Torfs, Paul

    2010-05-01

    Accurate flood forecasts have been a challenging topic in hydrology for decades. Uncertainty in hydrological forecasts is due to errors in initial state (e.g. forcing errors in historical mode), errors in model structure and parameters and last but not least the errors in model forcings (weather forecasts) during the forecast mode. More accurate flood forecasts can be obtained through data assimilation by merging observations with model simulations. This enables to identify the sources of uncertainties in the flood forecasting system. Our aim is to assess the different sources of error that affect the initial state and to investigate how they propagate through hydrological models with different levels of spatial variation, starting from lumped models. The knowledge thus obtained can then be used in a data assimilation scheme to improve the flood forecasts. This study presents the first results of this framework and focuses on quantifying precipitation errors and its effect on discharge simulations within the Ourthe catchment (1600 km2), which is situated in the Belgian Ardennes and is one of the larger subbasins of the Meuse River. Inside the catchment, hourly rain gauge information from 10 different locations is available over a period of 15 years. Based on these time series, the bootstrap method has been applied to generate precipitation ensembles. These were then used to simulate the catchment's discharges at the outlet. The corresponding streamflow ensembles were further assimilated with observed river discharges to update the model states of lumped hydrological models (R-PDM, HBV) through Residual Resampling. This particle filtering technique is a sequential data assimilation method and takes no prior assumption of the probability density function for the model states, which in contrast to the Ensemble Kalman filter does not have to be Gaussian. Our further research will be aimed at quantifying and reducing the sources of uncertainty that affect the initial

  13. Artificial Intelligence as a Business Forecasting and Error Handling Tool

    OpenAIRE

    Md. Tabrez Quasim; Rupak Chattopadhyay

    2015-01-01

     Any business enterprise must rely a lot on how well it can predict the future happenings. To cope up with the modern global customer demand, technological challenges, market competitions etc., any organization is compelled to foresee the future having maximum impact and least chances of errors. The traditional forecasting approaches have some limitations. That is why the business world is adopting the modern Artificial Intelligence based forecasting techniques. This paper has tried to presen...

  14. Influenza forecasting with Google Flu Trends.

    Science.gov (United States)

    Dugas, Andrea Freyer; Jalalpour, Mehdi; Gel, Yulia; Levin, Scott; Torcaso, Fred; Igusa, Takeru; Rothman, Richard E

    2013-01-01

    We developed a practical influenza forecast model based on real-time, geographically focused, and easy to access data, designed to provide individual medical centers with advanced warning of the expected number of influenza cases, thus allowing for sufficient time to implement interventions. Secondly, we evaluated the effects of incorporating a real-time influenza surveillance system, Google Flu Trends, and meteorological and temporal information on forecast accuracy. Forecast models designed to predict one week in advance were developed from weekly counts of confirmed influenza cases over seven seasons (2004-2011) divided into seven training and out-of-sample verification sets. Forecasting procedures using classical Box-Jenkins, generalized linear models (GLM), and generalized linear autoregressive moving average (GARMA) methods were employed to develop the final model and assess the relative contribution of external variables such as, Google Flu Trends, meteorological data, and temporal information. A GARMA(3,0) forecast model with Negative Binomial distribution integrating Google Flu Trends information provided the most accurate influenza case predictions. The model, on the average, predicts weekly influenza cases during 7 out-of-sample outbreaks within 7 cases for 83% of estimates. Google Flu Trend data was the only source of external information to provide statistically significant forecast improvements over the base model in four of the seven out-of-sample verification sets. Overall, the p-value of adding this external information to the model is 0.0005. The other exogenous variables did not yield a statistically significant improvement in any of the verification sets. Integer-valued autoregression of influenza cases provides a strong base forecast model, which is enhanced by the addition of Google Flu Trends confirming the predictive capabilities of search query based syndromic surveillance. This accessible and flexible forecast model can be used by

  15. Establishment of Health Technology Assessment in Iran

    Directory of Open Access Journals (Sweden)

    Shila Doaee

    2012-06-01

    Full Text Available Objective: Health Technology Assessment (HTA aims at informing healthcare policymakers, managers and practitioners of the "clinical consequences, but also the economic, ethical, and other social implications of the diffusion and use of a specific procedure or technique on medical practice". So considering the policy-oriented nature of HTA that calls for a close integration into the functioning and governance of health systems the present study focuses on executive processes and function of the HTA office of Iran.Materials and methods: Data of this review study were collected through documented sources and observations from 2007 to 2010.Results: Health Technology Assessment began its activities as a secretariat in the Deputy of Health in 2007 and it continues as a Health Technology Assessment Office at the Management of Health Technology Assessment, Standardization, and Tariff at the Deputy of curative affairs of MOHME in the beginning of 2010.14 Technology of modern medical equipment and 8 pharmaceutical medicine are assessed, Now many of measures for HTA establishment  such as cooperation National Institute of Health Research (NIHR, Holding scientific committee meetings, Establishing  the  Master's degree of  health technology assessment ,Building capacities for health technology assessment through education in major universities of the country.Conclusion: pay attention to health technology assessment, selection and application of proper technologies in the frameworks of policy-making and managerial strategies and make efforts to develop it with the support of the governmental in Iran is necessary.

  16. Probabilistic Price Forecasting for Day-Ahead and Intraday Markets: Beyond the Statistical Model

    Directory of Open Access Journals (Sweden)

    José R. Andrade

    2017-10-01

    Full Text Available Forecasting the hourly spot price of day-ahead and intraday markets is particularly challenging in electric power systems characterized by high installed capacity of renewable energy technologies. In particular, periods with low and high price levels are difficult to predict due to a limited number of representative cases in the historical dataset, which leads to forecast bias problems and wide forecast intervals. Moreover, these markets also require the inclusion of multiple explanatory variables, which increases the complexity of the model without guaranteeing a forecasting skill improvement. This paper explores information from daily futures contract trading and forecast of the daily average spot price to correct point and probabilistic forecasting bias. It also shows that an adequate choice of explanatory variables and use of simple models like linear quantile regression can lead to highly accurate spot price point and probabilistic forecasts. In terms of point forecast, the mean absolute error was 3.03 €/MWh for day-ahead market and a maximum value of 2.53 €/MWh was obtained for intraday session 6. The probabilistic forecast results show sharp forecast intervals and deviations from perfect calibration below 7% for all market sessions.

  17. Initial assessment of a multi-model approach to spring flood forecasting in Sweden

    Science.gov (United States)

    Olsson, J.; Uvo, C. B.; Foster, K.; Yang, W.

    2015-06-01

    Hydropower is a major energy source in Sweden and proper reservoir management prior to the spring flood onset is crucial for optimal production. This requires useful forecasts of the accumulated discharge in the spring flood period (i.e. the spring-flood volume, SFV). Today's SFV forecasts are generated using a model-based climatological ensemble approach, where time series of precipitation and temperature from historical years are used to force a calibrated and initialised set-up of the HBV model. In this study, a number of new approaches to spring flood forecasting, that reflect the latest developments with respect to analysis and modelling on seasonal time scales, are presented and evaluated. Three main approaches, represented by specific methods, are evaluated in SFV hindcasts for three main Swedish rivers over a 10-year period with lead times between 0 and 4 months. In the first approach, historically analogue years with respect to the climate in the period preceding the spring flood are identified and used to compose a reduced ensemble. In the second, seasonal meteorological ensemble forecasts are used to drive the HBV model over the spring flood period. In the third approach, statistical relationships between SFV and the large-sale atmospheric circulation are used to build forecast models. None of the new approaches consistently outperform the climatological ensemble approach, but for specific locations and lead times improvements of 20-30 % are found. When combining all forecasts in a weighted multi-model approach, a mean improvement over all locations and lead times of nearly 10 % was indicated. This demonstrates the potential of the approach and further development and optimisation into an operational system is ongoing.

  18. Forecasting telecommunication new service demand by analogy method and combined forecast

    Directory of Open Access Journals (Sweden)

    Lin Feng-Jenq

    2005-01-01

    Full Text Available In the modeling forecast field, we are usually faced with the more difficult problems of forecasting market demand for a new service or product. A new service or product is defined as that there is absence of historical data in this new market. We hardly use models to execute the forecasting work directly. In the Taiwan telecommunication industry, after liberalization in 1996, there are many new services opened continually. For optimal investment, it is necessary that the operators, who have been granted the concessions and licenses, forecast this new service within their planning process. Though there are some methods to solve or avoid this predicament, in this paper, we will propose one forecasting procedure that integrates the concept of analogy method and the idea of combined forecast to generate new service forecast. In view of the above, the first half of this paper describes the procedure of analogy method and the approach of combined forecast, and the second half provides the case of forecasting low-tier phone demand in Taiwan to illustrate this procedure's feasibility.

  19. Effect of Streamflow Forecast Uncertainty on Real-Time Reservoir Operation

    Science.gov (United States)

    Zhao, T.; Cai, X.; Yang, D.

    2010-12-01

    Various hydrological forecast products have been applied to real-time reservoir operation, including deterministic streamflow forecast (DSF), DSF-based probabilistic streamflow forecast (DPSF), and ensemble streamflow forecast (ESF), which represent forecast uncertainty in the form of deterministic forecast error, deterministic forecast error-based uncertainty distribution, and ensemble forecast errors, respectively. Compared to previous studies that treat these forecast products as ad hoc inputs for reservoir operation models, this paper attempts to model the uncertainties involved in the various forecast products and explores their effect on real-time reservoir operation decisions. In hydrology, there are various indices reflecting the magnitude of streamflow forecast uncertainty; meanwhile, few models illustrate the forecast uncertainty evolution process. This research introduces Martingale Model of Forecast Evolution (MMFE) from supply chain management and justifies its assumptions for quantifying the evolution of uncertainty in streamflow forecast as time progresses. Based on MMFE, this research simulates the evolution of forecast uncertainty in DSF, DPSF, and ESF, and applies the reservoir operation models (dynamic programming, DP; stochastic dynamic programming, SDP; and standard operation policy, SOP) to assess the effect of different forms of forecast uncertainty on real-time reservoir operation. Through a hypothetical single-objective real-time reservoir operation model, the results illustrate that forecast uncertainty exerts significant effects. Reservoir operation efficiency, as measured by a utility function, decreases as the forecast uncertainty increases. Meanwhile, these effects also depend on the type of forecast product being used. In general, the utility of reservoir operation with ESF is nearly as high as the utility obtained with a perfect forecast; the utilities of DSF and DPSF are similar to each other but not as efficient as ESF. Moreover

  20. Fuzzy approach for short term load forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Chenthur Pandian, S.; Duraiswamy, K.; Kanagaraj, N. [Electrical and Electronics Engg., K.S. Rangasamy College of Technology, Tiruchengode 637209, Tamil Nadu (India); Christober Asir Rajan, C. [Department of Electrical and Electronics Engineering, Pondicherry Engineering College, Pondicherry (India)

    2006-04-15

    The main objective of short term load forecasting (STLF) is to provide load predictions for generation scheduling, economic load dispatch and security assessment at any time. The STLF is needed to supply necessary information for the system management of day-to-day operations and unit commitment. In this paper, the 'time' and 'temperature' of the day are taken as inputs for the fuzzy logic controller and the 'forecasted load' is the output. The input variable 'time' has been divided into eight triangular membership functions. The membership functions are Mid Night, Dawn, Morning, Fore Noon, After Noon, Evening, Dusk and Night. Another input variable 'temperature' has been divided into four triangular membership functions. They are Below Normal, Normal, Above Normal and High. The 'forecasted load' as output has been divided into eight triangular membership functions. They are Very Low, Low, Sub Normal, Moderate Normal, Normal, Above Normal, High and Very High. Case studies have been carried out for the Neyveli Thermal Power Station Unit-II (NTPS-II) in India. The fuzzy forecasted load values are compared with the conventional forecasted values. The forecasted load closely matches the actual one within +/-3%. (author)

  1. Forecasting and management of technology

    National Research Council Canada - National Science Library

    Roper, A. T

    2011-01-01

    ... what the authors see as the innovations to technology management in the last 17 years: the Internet; the greater focus on group decision-making including process management and mechanism design; and desktop software that has transformed the analytical capabilities of technology managers"--Provided by publisher.

  2. Superconducting Technology Assessment

    National Research Council Canada - National Science Library

    2005-01-01

    This Superconducting Technology Assessment (STA) has been conducted by the National Security Agency to address the fundamental question of a potential replacement for silicon complementary metal oxide semiconductor (CMOS...

  3. Forecasting gaming revenues in Clark County, Nevada: Issues and methods

    Energy Technology Data Exchange (ETDEWEB)

    Edwards, B.K.; Bando, A.

    1992-01-01

    This paper describes the Western Area Gaming and Economic Response Simulator (WAGERS), a forecasting model that emphasizes the role of the gaming industry in Clark County, Nevada. Is is designed to generate forecasts of gaming revenues in Clark County, whose regional economy is dominated by the gaming industry. The model is meant to forecast Clark County gaming revenues and identifies the exogenous variables that affect gaming revenues. It will provide baseline forecasts of Clark County gaming revenues in order to assess changes in gaming-related economic activity resulting from changes in regional economic activity and tourism.

  4. Forecasting gaming revenues in Clark County, Nevada: Issues and methods

    Energy Technology Data Exchange (ETDEWEB)

    Edwards, B.K.; Bando, A.

    1992-07-01

    This paper describes the Western Area Gaming and Economic Response Simulator (WAGERS), a forecasting model that emphasizes the role of the gaming industry in Clark County, Nevada. Is is designed to generate forecasts of gaming revenues in Clark County, whose regional economy is dominated by the gaming industry. The model is meant to forecast Clark County gaming revenues and identifies the exogenous variables that affect gaming revenues. It will provide baseline forecasts of Clark County gaming revenues in order to assess changes in gaming-related economic activity resulting from changes in regional economic activity and tourism.

  5. Assessing the potential for improving S2S forecast skill through multimodel ensembling

    Science.gov (United States)

    Vigaud, N.; Robertson, A. W.; Tippett, M. K.; Wang, L.; Bell, M. J.

    2016-12-01

    Non-linear logistic regression is well suited to probability forecasting and has been successfully applied in the past to ensemble weather and climate predictions, providing access to the full probabilities distribution without any Gaussian assumption. However, little work has been done at sub-monthly lead times where relatively small re-forecast ensembles and lengths represent new challenges for which post-processing avenues have yet to be investigated. A promising approach consists in extending the definition of non-linear logistic regression by including the quantile of the forecast distribution as one of the predictors. So-called Extended Logistic Regression (ELR), which enables mutually consistent individual threshold probabilities, is here applied to ECMWF, CFSv2 and CMA re-forecasts from the S2S database in order to produce rainfall probabilities at weekly resolution. The ELR model is trained on seasonally-varying tercile categories computed for lead times of 1 to 4 weeks. It is then tested in a cross-validated manner, i.e. allowing real-time predictability applications, to produce rainfall tercile probabilities from individual weekly hindcasts that are finally combined by equal pooling. Results will be discussed over a broader North American region, where individual and MME forecasts generated out to 4 weeks lead are characterized by good probabilistic reliability but low sharpness, exhibiting systematically more skill in winter than summer.

  6. Waste Information Management System with Integrated Transportation Forecast Data

    International Nuclear Information System (INIS)

    Upadhyay, H.; Quintero, W.; Shoffner, P.; Lagos, L.

    2009-01-01

    The Waste Information Management System with Integrated Transportation Forecast Data was developed to support the Department of Energy (DOE) mandated accelerated cleanup program. The schedule compression required close coordination and a comprehensive review and prioritization of the barriers that impeded treatment and disposition of the waste streams at each site. Many issues related to site waste treatment and disposal were potential critical path issues under the accelerated schedules. In order to facilitate accelerated cleanup initiatives, waste managers at DOE field sites and at DOE Headquarters in Washington, D.C., needed timely waste forecast and transportation information regarding the volumes and types of waste that would be generated by the DOE sites over the next 40 years. Each local DOE site has historically collected, organized, and displayed site waste forecast information in separate and unique systems. However, waste and shipment information from all sites needed a common application to allow interested parties to understand and view the complete complex-wide picture. The Waste Information Management System with Integrated Transportation Forecast Data allows identification of total forecasted waste volumes, material classes, disposition sites, choke points, technological or regulatory barriers to treatment and disposal, along with forecasted waste transportation information by rail, truck and inter-modal shipments. The Applied Research Center (ARC) at Florida International University (FIU) in Miami, Florida, has deployed the web-based forecast and transportation system and is responsible for updating the waste forecast and transportation data on a regular basis to ensure the long-term viability and value of this system. (authors)

  7. Development of Hydrometeorological Monitoring and Forecasting as AN Essential Component of the Early Flood Warning System:

    Science.gov (United States)

    Manukalo, V.

    2012-12-01

    Defining issue The river inundations are the most common and destructive natural hazards in Ukraine. Among non-structural flood management and protection measures a creation of the Early Flood Warning System is extremely important to be able to timely recognize dangerous situations in the flood-prone areas. Hydrometeorological information and forecasts are a core importance in this system. The primary factors affecting reliability and a lead - time of forecasts include: accuracy, speed and reliability with which real - time data are collected. The existing individual conception of monitoring and forecasting resulted in a need in reconsideration of the concept of integrated monitoring and forecasting approach - from "sensors to database and forecasters". Result presentation The Project: "Development of Flood Monitoring and Forecasting in the Ukrainian part of the Dniester River Basin" is presented. The project is developed by the Ukrainian Hydrometeorological Service in a conjunction with the Water Management Agency and the Energy Company "Ukrhydroenergo". The implementation of the Project is funded by the Ukrainian Government and the World Bank. The author is nominated as the responsible person for coordination of activity of organizations involved in the Project. The term of the Project implementation: 2012 - 2014. The principal objectives of the Project are: a) designing integrated automatic hydrometeorological measurement network (including using remote sensing technologies); b) hydrometeorological GIS database construction and coupling with electronic maps for flood risk assessment; c) interface-construction classic numerical database -GIS and with satellite images, and radar data collection; d) providing the real-time data dissemination from observation points to forecasting centers; e) developing hydrometeoroogical forecasting methods; f) providing a flood hazards risk assessment for different temporal and spatial scales; g) providing a dissemination of

  8. Forecasting the value of credit scoring

    Science.gov (United States)

    Saad, Shakila; Ahmad, Noryati; Jaffar, Maheran Mohd

    2017-08-01

    Nowadays, credit scoring system plays an important role in banking sector. This process is important in assessing the creditworthiness of customers requesting credit from banks or other financial institutions. Usually, the credit scoring is used when customers send the application for credit facilities. Based on the score from credit scoring, bank will be able to segregate the "good" clients from "bad" clients. However, in most cases the score is useful at that specific time only and cannot be used to forecast the credit worthiness of the same applicant after that. Hence, bank will not know if "good" clients will always be good all the time or "bad" clients may become "good" clients after certain time. To fill up the gap, this study proposes an equation to forecast the credit scoring of the potential borrowers at a certain time by using the historical score related to the assumption. The Mean Absolute Percentage Error (MAPE) is used to measure the accuracy of the forecast scoring. Result shows the forecast scoring is highly accurate as compared to actual credit scoring.

  9. Evaluation of the Plant-Craig stochastic convection scheme in an ensemble forecasting system

    Science.gov (United States)

    Keane, R. J.; Plant, R. S.; Tennant, W. J.

    2015-12-01

    The Plant-Craig stochastic convection parameterization (version 2.0) is implemented in the Met Office Regional Ensemble Prediction System (MOGREPS-R) and is assessed in comparison with the standard convection scheme with a simple stochastic element only, from random parameter variation. A set of 34 ensemble forecasts, each with 24 members, is considered, over the month of July 2009. Deterministic and probabilistic measures of the precipitation forecasts are assessed. The Plant-Craig parameterization is found to improve probabilistic forecast measures, particularly the results for lower precipitation thresholds. The impact on deterministic forecasts at the grid scale is neutral, although the Plant-Craig scheme does deliver improvements when forecasts are made over larger areas. The improvements found are greater in conditions of relatively weak synoptic forcing, for which convective precipitation is likely to be less predictable.

  10. Technologies Assessing Limb Bradykinesia in Parkinson's Disease.

    Science.gov (United States)

    Hasan, Hasan; Athauda, Dilan S; Foltynie, Thomas; Noyce, Alastair J

    2017-01-01

    The MDS-UPDRS (Movement Disorders Society - Unified Parkinson's Disease Rating Scale) is the most widely used scale for rating impairment in PD. Subscores measuring bradykinesia have low reliability that can be subject to rater variability. Novel technological tools can be used to overcome such issues. To systematically explore and describe the available technologies for measuring limb bradykinesia in PD that were published between 2006 and 2016. A systematic literature search using PubMed (MEDLINE), IEEE Xplore, Web of Science, Scopus and Engineering Village (Compendex and Inspec) databases was performed to identify relevant technologies published until 18 October 2016. 47 technologies assessing bradykinesia in PD were identified, 17 of which offered home and clinic-based assessment whilst 30 provided clinic-based assessment only. Of the eligible studies, 7 were validated in a PD patient population only, whilst 40 were tested in both PD and healthy control groups. 19 of the 47 technologies assessed bradykinesia only, whereas 28 assessed other parkinsonian features as well. 33 technologies have been described in additional PD-related studies, whereas 14 are not known to have been tested beyond the pilot phase. Technology based tools offer advantages including objective motor assessment and home monitoring of symptoms, and can be used to assess response to intervention in clinical trials or routine care. This review provides an up-to-date repository and synthesis of the current literature regarding technology used for assessing limb bradykinesia in PD. The review also discusses the current trends with regards to technology and discusses future directions in development.

  11. Latin America wind market assessment. Forecast 2013-2022

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2013-10-15

    Wind Power Activities by Country: Developers/Owners, Wind Plant Sizes, Wind Turbines Deployed, Commissioning Dates, Market Share, and Capacity Forecasts Latin American markets are a subject of intense interest from the global wind industry. Wind plant construction across Latin America is modest compared to the more established markets like the United States, Europe, and China, but it is an emerging market that is taking off at a rapid pace. The region has become the hottest alternative growth market for the wind energy industry at a time when growth rates in other markets are flat due to a variety of policy and macroeconomic challenges. Globalization is driving sustainable economic growth in most Latin American countries, resulting in greater energy demand. Wind is increasingly viewed as a valuable and essential answer to increasing electricity generation across most markets in Latin America. Strong wind resources, coupled with today's sophisticated wind turbines, are providing cost-effective generation that is competitive with fossil fuel generation. Most Latin American countries also rely heavily on hydroelectricity, which balances well with variable wind generation. Navigant Research forecasts that if most wind plants under construction with planned commissioning go online as scheduled, annual wind power installations in Latin America will grow from nearly 2.2 GW in 2013 to 4.3 GW by 2022. This Navigant Research report provides a comprehensive view of the wind energy market dynamics at play in Latin America. It offers a country-by-country analysis, outlining the key energy policies and development opportunities and barriers and identifying which companies own operational wind plants and which wind turbine vendors supplied those projects. Market forecasts for wind power installations, capacity, and market share in Latin America, segmented by country and company, extend through 2022. The report also offers an especially close analysis of Brazil and Mexico

  12. How to judge the quality and value of weather forecast products

    Science.gov (United States)

    Thornes, John E.; Stephenson, David B.

    2001-09-01

    In order to decide whether or not a weather service supplier is giving good value for money we need to monitor the quality of the forecasts and the use that is made of the forecasts to estimate their value. A number of verification statistics are examined to measure the quality of forecasts - including Miss Rate, False Alarm Rate, the Peirce Skill Score and the Odds Ratio Skill Score - and a means of testing the significance of these values is presented. In order to assess the economic value of the forecasts a value index is suggested that takes into account the cost-loss ratio and forecast errors. It is suggested that a combination of these quality and value statistics could be used by weather forecast customers to choose the best forecast provider and to set limits for performance related contracts.

  13. THE ACCURACY AND BIAS EVALUATION OF THE USA UNEMPLOYMENT RATE FORECASTS. METHODS TO IMPROVE THE FORECASTS ACCURACY

    Directory of Open Access Journals (Sweden)

    MIHAELA BRATU (SIMIONESCU

    2012-12-01

    Full Text Available In this study some alternative forecasts for the unemployment rate of USA made by four institutions (International Monetary Fund (IMF, Organization for Economic Co-operation and Development (OECD, Congressional Budget Office (CBO and Blue Chips (BC are evaluated regarding the accuracy and the biasness. The most accurate predictions on the forecasting horizon 201-2011 were provided by IMF, followed by OECD, CBO and BC.. These results were gotten using U1 Theil’s statistic and a new method that has not been used before in literature in this context. The multi-criteria ranking was applied to make a hierarchy of the institutions regarding the accuracy and five important accuracy measures were taken into account at the same time: mean errors, mean squared error, root mean squared error, U1 and U2 statistics of Theil. The IMF, OECD and CBO predictions are unbiased. The combined forecasts of institutions’ predictions are a suitable strategy to improve the forecasts accuracy of IMF and OECD forecasts when all combination schemes are used, but INV one is the best. The filtered and smoothed original predictions based on Hodrick-Prescott filter, respectively Holt-Winters technique are a good strategy of improving only the BC expectations. The proposed strategies to improve the accuracy do not solve the problem of biasness. The assessment and improvement of forecasts accuracy have an important contribution in growing the quality of decisional process.

  14. Performance and Quality Assessment of the Forthcoming Copernicus Marine Service Global Ocean Monitoring and Forecasting Real-Time System

    Science.gov (United States)

    Lellouche, J. M.; Le Galloudec, O.; Greiner, E.; Garric, G.; Regnier, C.; Drillet, Y.

    2016-02-01

    Mercator Ocean currently delivers in real-time daily services (weekly analyses and daily forecast) with a global 1/12° high resolution system. The model component is the NEMO platform driven at the surface by the IFS ECMWF atmospheric analyses and forecasts. Observations are assimilated by means of a reduced-order Kalman filter with a 3D multivariate modal decomposition of the forecast error. It includes an adaptive-error estimate and a localization algorithm. Along track altimeter data, satellite Sea Surface Temperature and in situ temperature and salinity vertical profiles are jointly assimilated to estimate the initial conditions for numerical ocean forecasting. A 3D-Var scheme provides a correction for the slowly-evolving large-scale biases in temperature and salinity.Since May 2015, Mercator Ocean opened the Copernicus Marine Service (CMS) and is in charge of the global ocean analyses and forecast, at eddy resolving resolution. In this context, R&D activities have been conducted at Mercator Ocean these last years in order to improve the real-time 1/12° global system for the next CMS version in 2016. The ocean/sea-ice model and the assimilation scheme benefit among others from the following improvements: large-scale and objective correction of atmospheric quantities with satellite data, new Mean Dynamic Topography taking into account the last version of GOCE geoid, new adaptive tuning of some observational errors, new Quality Control on the assimilated temperature and salinity vertical profiles based on dynamic height criteria, assimilation of satellite sea-ice concentration, new freshwater runoff from ice sheets melting …This presentation doesn't focus on the impact of each update, but rather on the overall behavior of the system integrating all updates. This assessment reports on the products quality improvements, highlighting the level of performance and the reliability of the new system.

  15. A national-scale seasonal hydrological forecast system: development and evaluation over Britain

    Directory of Open Access Journals (Sweden)

    V. A. Bell

    2017-09-01

    Full Text Available Skilful winter seasonal predictions for the North Atlantic circulation and northern Europe have now been demonstrated and the potential for seasonal hydrological forecasting in the UK is now being explored. One of the techniques being used combines seasonal rainfall forecasts provided by operational weather forecast systems with hydrological modelling tools to provide estimates of seasonal mean river flows up to a few months ahead. The work presented here shows how spatial information contained in a distributed hydrological model typically requiring high-resolution (daily or better rainfall data can be used to provide an initial condition for a much simpler forecast model tailored to use low-resolution monthly rainfall forecasts. Rainfall forecasts (hindcasts from the GloSea5 model (1996 to 2009 are used to provide the first assessment of skill in these national-scale flow forecasts. The skill in the combined modelling system is assessed for different seasons and regions of Britain, and compared to what might be achieved using other approaches such as use of an ensemble of historical rainfall in a hydrological model, or a simple flow persistence forecast. The analysis indicates that only limited forecast skill is achievable for Spring and Summer seasonal hydrological forecasts; however, Autumn and Winter flows can be reasonably well forecast using (ensemble mean rainfall forecasts based on either GloSea5 forecasts or historical rainfall (the preferred type of forecast depends on the region. Flow forecasts using ensemble mean GloSea5 rainfall perform most consistently well across Britain, and provide the most skilful forecasts overall at the 3-month lead time. Much of the skill (64 % in the 1-month ahead seasonal flow forecasts can be attributed to the hydrological initial condition (particularly in regions with a significant groundwater contribution to flows, whereas for the 3-month ahead lead time, GloSea5 forecasts account for  ∼ 70

  16. A Condition Based Maintenance Approach to Forecasting B-1 Aircraft Parts

    Science.gov (United States)

    2017-03-23

    Air Force Institute of Technology AFIT Scholar Theses and Dissertations 3-23-2017 A Condition Based Maintenance Approach to Forecasting B-1 Aircraft...component’s life history where reliability forecasts could be stipulated based on a component’s current condition . One of the major issues their report noted...Engine Condition Monitoring System Specification. Contract Number DOT-CG-80513-A. Grand Prairie, TX. Air Force Materiel Command. (2011) Requirements For

  17. Technology data characterizing water heating in commercial buildings: Application to end-use forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Sezgen, O.; Koomey, J.G.

    1995-12-01

    Commercial-sector conservation analyses have traditionally focused on lighting and space conditioning because of their relatively-large shares of electricity and fuel consumption in commercial buildings. In this report we focus on water heating, which is one of the neglected end uses in the commercial sector. The share of the water-heating end use in commercial-sector electricity consumption is 3%, which corresponds to 0.3 quadrillion Btu (quads) of primary energy consumption. Water heating accounts for 15% of commercial-sector fuel use, which corresponds to 1.6 quads of primary energy consumption. Although smaller in absolute size than the savings associated with lighting and space conditioning, the potential cost-effective energy savings from water heaters are large enough in percentage terms to warrant closer attention. In addition, water heating is much more important in particular building types than in the commercial sector as a whole. Fuel consumption for water heating is highest in lodging establishments, hospitals, and restaurants (0.27, 0.22, and 0.19 quads, respectively); water heating`s share of fuel consumption for these building types is 35%, 18% and 32%, respectively. At the Lawrence Berkeley National Laboratory, we have developed and refined a base-year data set characterizing water heating technologies in commercial buildings as well as a modeling framework. We present the data and modeling framework in this report. The present commercial floorstock is characterized in terms of water heating requirements and technology saturations. Cost-efficiency data for water heating technologies are also developed. These data are intended to support models used for forecasting energy use of water heating in the commercial sector.

  18. Forecasting Container Throughput at the Doraleh Port in Djibouti through Time Series Analysis

    Science.gov (United States)

    Mohamed Ismael, Hawa; Vandyck, George Kobina

    The Doraleh Container Terminal (DCT) located in Djibouti has been noted as the most technologically advanced container terminal on the African continent. DCT's strategic location at the crossroads of the main shipping lanes connecting Asia, Africa and Europe put it in a unique position to provide important shipping services to vessels plying that route. This paper aims to forecast container throughput through the Doraleh Container Port in Djibouti by Time Series Analysis. A selection of univariate forecasting models has been used, namely Triple Exponential Smoothing Model, Grey Model and Linear Regression Model. By utilizing the above three models and their combination, the forecast of container throughput through the Doraleh port was realized. A comparison of the different forecasting results of the three models, in addition to the combination forecast is then undertaken, based on commonly used evaluation criteria Mean Absolute Deviation (MAD) and Mean Absolute Percentage Error (MAPE). The study found that the Linear Regression forecasting Model was the best prediction method for forecasting the container throughput, since its forecast error was the least. Based on the regression model, a ten (10) year forecast for container throughput at DCT has been made.

  19. Technological and life cycle assessment of organics processing odour control technologies

    Energy Technology Data Exchange (ETDEWEB)

    Bindra, Navin [School of Engineering, University of Guelph, 50 Stone Road East, Guelph, Ontario N1G2W1 (Canada); Dubey, Brajesh, E-mail: bkdubey@civil.iitkgp.ernet.in [School of Engineering, University of Guelph, 50 Stone Road East, Guelph, Ontario N1G2W1 (Canada); Environmental Engineering Division, Department of Civil Engineering, Indian Institute of Technology, Kharagpur, West Bengal 721302 (India); Dutta, Animesh [School of Engineering, University of Guelph, 50 Stone Road East, Guelph, Ontario N1G2W1 (Canada)

    2015-09-15

    As more municipalities and communities across developed world look towards implementing organic waste management programmes or upgrading existing ones, composting facilities are emerging as a popular choice. However, odour from these facilities continues to be one of the most important concerns in terms of cost & effective mitigation. This paper provides a technological and life cycle assessment of some of the different odour control technologies and treatment methods that can be implemented in organics processing facilities. The technological assessment compared biofilters, packed tower wet scrubbers, fine mist wet scrubbers, activated carbon adsorption, thermal oxidization, oxidization chemicals and masking agents. The technologies/treatment methods were evaluated and compared based on a variety of operational, usage and cost parameters. Based on the technological assessment it was found that, biofilters and packed bed wet scrubbers are the most applicable odour control technologies for use in organics processing faculties. A life cycle assessment was then done to compare the environmental impacts of the packed-bed wet scrubber system, organic (wood-chip media) bio-filter and inorganic (synthetic media) bio-filter systems. Twelve impact categories were assessed; cumulative energy demand (CED), climate change, human toxicity, photochemical oxidant formation, metal depletion, fossil depletion, terrestrial acidification, freshwater eutrophication, marine eutrophication, terrestrial eco-toxicity, freshwater eco-toxicity and marine eco-toxicity. The results showed that for all impact categories the synthetic media biofilter had the highest environmental impact, followed by the wood chip media bio-filter system. The packed-bed system had the lowest environmental impact for all categories. - Highlights: • Assessment of odour control technologies for organics processing facilities. • Comparative life cycle assessment of three odour control technologies was conducted

  20. A global flash flood forecasting system

    Science.gov (United States)

    Baugh, Calum; Pappenberger, Florian; Wetterhall, Fredrik; Hewson, Tim; Zsoter, Ervin

    2016-04-01

    The sudden and devastating nature of flash flood events means it is imperative to provide early warnings such as those derived from Numerical Weather Prediction (NWP) forecasts. Currently such systems exist on basin, national and continental scales in Europe, North America and Australia but rely on high resolution NWP forecasts or rainfall-radar nowcasting, neither of which have global coverage. To produce global flash flood forecasts this work investigates the possibility of using forecasts from a global NWP system. In particular we: (i) discuss how global NWP can be used for flash flood forecasting and discuss strengths and weaknesses; (ii) demonstrate how a robust evaluation can be performed given the rarity of the event; (iii) highlight the challenges and opportunities in communicating flash flood uncertainty to decision makers; and (iv) explore future developments which would significantly improve global flash flood forecasting. The proposed forecast system uses ensemble surface runoff forecasts from the ECMWF H-TESSEL land surface scheme. A flash flood index is generated using the ERIC (Enhanced Runoff Index based on Climatology) methodology [Raynaud et al., 2014]. This global methodology is applied to a series of flash floods across southern Europe. Results from the system are compared against warnings produced using the higher resolution COSMO-LEPS limited area model. The global system is evaluated by comparing forecasted warning locations against a flash flood database of media reports created in partnership with floodlist.com. To deal with the lack of objectivity in media reports we carefully assess the suitability of different skill scores and apply spatial uncertainty thresholds to the observations. To communicate the uncertainties of the flash flood system output we experiment with a dynamic region-growing algorithm. This automatically clusters regions of similar return period exceedence probabilities, thus presenting the at-risk areas at a spatial

  1. Powering Up With Space-Time Wind Forecasting

    KAUST Repository

    Hering, Amanda S.

    2010-03-01

    The technology to harvest electricity from wind energy is now advanced enough to make entire cities powered by it a reality. High-quality, short-term forecasts of wind speed are vital to making this a more reliable energy source. Gneiting et al. (2006) have introduced a model for the average wind speed two hours ahead based on both spatial and temporal information. The forecasts produced by this model are accurate, and subject to accuracy, the predictive distribution is sharp, that is, highly concentrated around its center. However, this model is split into nonunique regimes based on the wind direction at an offsite location. This paper both generalizes and improves upon this model by treating wind direction as a circular variable and including it in the model. It is robust in many experiments, such as predicting wind at other locations. We compare this with the more common approach of modeling wind speeds and directions in the Cartesian space and use a skew-t distribution for the errors. The quality of the predictions from all of these models can be more realistically assessed with a loss measure that depends upon the power curve relating wind speed to power output. This proposed loss measure yields more insight into the true value of each models predictions. © 2010 American Statistical Association.

  2. Powering Up With Space-Time Wind Forecasting

    KAUST Repository

    Hering, Amanda S.; Genton, Marc G.

    2010-01-01

    The technology to harvest electricity from wind energy is now advanced enough to make entire cities powered by it a reality. High-quality, short-term forecasts of wind speed are vital to making this a more reliable energy source. Gneiting et al. (2006) have introduced a model for the average wind speed two hours ahead based on both spatial and temporal information. The forecasts produced by this model are accurate, and subject to accuracy, the predictive distribution is sharp, that is, highly concentrated around its center. However, this model is split into nonunique regimes based on the wind direction at an offsite location. This paper both generalizes and improves upon this model by treating wind direction as a circular variable and including it in the model. It is robust in many experiments, such as predicting wind at other locations. We compare this with the more common approach of modeling wind speeds and directions in the Cartesian space and use a skew-t distribution for the errors. The quality of the predictions from all of these models can be more realistically assessed with a loss measure that depends upon the power curve relating wind speed to power output. This proposed loss measure yields more insight into the true value of each models predictions. © 2010 American Statistical Association.

  3. Remote Sensing Technologies and Geospatial Modelling Hierarchy for Smart City Support

    Science.gov (United States)

    Popov, M.; Fedorovsky, O.; Stankevich, S.; Filipovich, V.; Khyzhniak, A.; Piestova, I.; Lubskyi, M.; Svideniuk, M.

    2017-12-01

    The approach to implementing the remote sensing technologies and geospatial modelling for smart city support is presented. The hierarchical structure and basic components of the smart city information support subsystem are considered. Some of the already available useful practical developments are described. These include city land use planning, urban vegetation analysis, thermal condition forecasting, geohazard detection, flooding risk assessment. Remote sensing data fusion approach for comprehensive geospatial analysis is discussed. Long-term city development forecasting by Forrester - Graham system dynamics model is provided over Kiev urban area.

  4. Forecasting military expenditure

    Directory of Open Access Journals (Sweden)

    Tobias Böhmelt

    2014-05-01

    Full Text Available To what extent do frequently cited determinants of military spending allow us to predict and forecast future levels of expenditure? The authors draw on the data and specifications of a recent model on military expenditure and assess the predictive power of its variables using in-sample predictions, out-of-sample forecasts and Bayesian model averaging. To this end, this paper provides guidelines for prediction exercises in general using these three techniques. More substantially, however, the findings emphasize that previous levels of military spending as well as a country’s institutional and economic characteristics particularly improve our ability to predict future levels of investment in the military. Variables pertaining to the international security environment also matter, but seem less important. In addition, the results highlight that the updated model, which drops weak predictors, is not only more parsimonious, but also slightly more accurate than the original specification.

  5. Inflation Forecast Contracts

    OpenAIRE

    Gersbach, Hans; Hahn, Volker

    2012-01-01

    We introduce a new type of incentive contract for central bankers: inflation forecast contracts, which make central bankers’ remunerations contingent on the precision of their inflation forecasts. We show that such contracts enable central bankers to influence inflation expectations more effectively, thus facilitating more successful stabilization of current inflation. Inflation forecast contracts improve the accuracy of inflation forecasts, but have adverse consequences for output. On balanc...

  6. Technology assessment of solar energy utilization

    Science.gov (United States)

    Jaeger, F.

    1985-11-01

    The general objectives and methods of Technology Assessment (TA) are outlined. Typical analysis steps of a TA for solar energy are reviewed: description of the technology and its further development; identification of impact areas; analysis of boundary conditions and definition of scenarios; market penetration of solar technologies; projection of consequences in areas of impact; and assessment of impacts and identification of options for action.

  7. Issues in midterm analysis and forecasting, 1996

    International Nuclear Information System (INIS)

    1996-08-01

    This document consists of papers which cover topics in analysis and modeling that underlie the Annual Energy Outlook 1996. Topics include: The Potential Impact of Technological Progress on U.S. Energy Markets; The Outlook for U.S. Import Dependence; Fuel Economy, Vehicle Choice, and Changing Demographics, and Annual Energy Outlook Forecast Evaluation

  8. Forecasting short-term wind farm production in complex terrain. Volume 1

    International Nuclear Information System (INIS)

    LeBlanc, M.

    2005-01-01

    Wind energy forecasting adds financial value to wind farms and may soon become a regulatory requirement. A robust information technology system is essential for addressing industry demands. Various forecasting methodologies for short-term wind production in complex terrain were presented. Numerical weather predictions were discussed with reference to supervisory control and data acquisition (SCADA) system site measurements. Forecasting methods using wind speed, direction, temperature and pressure, as well as issues concerning statistical modelling were presented. Model output statistics and neural networks were reviewed, as well as significant components of error. Results from a Garrad Hassan forecaster with a European wind farm were presented, including wind speed evaluation, and forecast horizon for T + 1 hours, T + 12 hours, and T + 36 hours. It was suggested that buy prices often reflect the cost of under-prediction, and that forecasting has more potential where the spread is greatest. Accurate T + 19 hours to T + 31 hours could enable participation in the day-ahead market, which is less volatile and prices are usually better. Estimates of possible profits per annum through the use of GH forecaster power predictions were presented, calculated over and above spilling power to the grid. It was concluded that accurate forecasts combined with certainty evaluation enables the optimization of wind energy in the market, and is applicable to a wide range of weather regimes and terrain types. It was suggested that site feedback is essential for good forecasts at short horizons, and that the value of forecasting is dependent on the market. refs., tabs., figs

  9. Medium Range Flood Forecasting for Agriculture Damage Reduction

    Science.gov (United States)

    Fakhruddin, S. H. M.

    2014-12-01

    Early warning is a key element for disaster risk reduction. In recent decades, major advancements have been made in medium range and seasonal flood forecasting. This progress provides a great opportunity to reduce agriculture damage and improve advisories for early action and planning for flood hazards. This approach can facilitate proactive rather than reactive management of the adverse consequences of floods. In the agricultural sector, for instance, farmers can take a diversity of options such as changing cropping patterns, applying fertilizer, irrigating and changing planting timing. An experimental medium range (1-10 day) flood forecasting model has been developed for Bangladesh and Thailand. It provides 51 sets of discharge ensemble forecasts of 1-10 days with significant persistence and high certainty. This type of forecast could assist farmers and other stakeholders for differential preparedness activities. These ensembles probabilistic flood forecasts have been customized based on user-needs for community-level application focused on agriculture system. The vulnerabilities of agriculture system were calculated based on exposure, sensitivity and adaptive capacity. Indicators for risk and vulnerability assessment were conducted through community consultations. The forecast lead time requirement, user-needs, impacts and management options for crops were identified through focus group discussions, informal interviews and community surveys. This paper illustrates potential applications of such ensembles for probabilistic medium range flood forecasts in a way that is not commonly practiced globally today.

  10. Drug delivery system innovation and Health Technology Assessment: Upgrading from Clinical to Technological Assessment.

    Science.gov (United States)

    Panzitta, Michele; Bruno, Giorgio; Giovagnoli, Stefano; Mendicino, Francesca R; Ricci, Maurizio

    2015-11-30

    Health Technology Assessment (HTA) is a multidisciplinary health political instrument that evaluates the consequences, mainly clinical and economical, of a health care technology; the HTA aim is to produce and spread information on scientific and technological innovation for health political decision making process. Drug delivery systems (DDS), such as nanocarriers, are technologically complex but they have pivotal relevance in therapeutic innovation. The HTA process, as commonly applied to conventional drug evaluation, should upgrade to a full pharmaceutical assessment, considering the DDS complexity. This is useful to study more in depth the clinical outcome and to broaden its critical assessment toward pharmaceutical issues affecting the patient and not measured by the current clinical evidence approach. We draw out the expertise necessary to perform the pharmaceutical assessment and we propose a format to evaluate the DDS technological topics such as formulation and mechanism of action, physicochemical characteristics, manufacturing process. We integrated the above-mentioned three points in the Evidence Based Medicine approach, which is data source for any HTA process. In this regard, the introduction of a Pharmaceutics Expert figure in the HTA could be fundamental to grant a more detailed evaluation of medicine product characteristics and performances and to help optimizing DDS features to overcome R&D drawbacks. Some aspects of product development, such as manufacturing processes, should be part of the HTA as innovative manufacturing processes allow new products to reach more effectively patient bedside. HTA so upgraded may encourage resource allocating payers to invest in innovative technologies and providers to focus on innovative material properties and manufacturing processes, thus contributing to bring more medicines in therapy in a sustainable manner. Copyright © 2015 Elsevier B.V. All rights reserved.

  11. Forecast analysis of the electricity supply-demand balance in France for summer 2013

    International Nuclear Information System (INIS)

    2013-05-01

    Under normal meteorological conditions, and notwithstanding localized risks associated with the vulnerability of certain regions, the forecast outlook for the electricity supply-demand balance in continental France shows no particular risk for the entire summer 2013 period. Special vigilance is maintained in the Provence-Alpes-Cote d'Azur region, given the risk of forest fires and potential outages affecting the dual 400 kV link from Toulon. This assessment is based on the assumption that forecast demand for summer 2013 will remain broadly stable as compared with summer 2012, given public economic indicators, but also that the forecast availability of the French generating fleet will increase by 1100 MW compared with summer 2012. This increased availability is based on information supplied by generators, and notably includes scheduled temporary outages of certain combined cycle gas turbines. Finally, growth in photovoltaic generation (3,700 MW of installed capacity currently in France) is continuing at a sustained pace, leading to a 700 MW increase in the mean availability rate for this generation technology as compared with summer 2012. Moreover, the substantial investments already made by RTE or currently in progress to develop its network (voltage support measures, Cotentin-Maine line, etc.) have had a very positive impact on the reliability of the power system. (authors)

  12. Entity’s Irregular Demand Scheduling of the Wholesale Electricity Market based on the Forecast of Hourly Price Ratios

    Directory of Open Access Journals (Sweden)

    O. V. Russkov

    2015-01-01

    Full Text Available The article considers a hot issue to forecast electric power demand amounts and prices for the entities of wholesale electricity market (WEM, which are in capacity of a large user with production technology requirements prevailing over hourly energy planning ones. An electric power demand of such entities is on irregular schedule. The article analyses mathematical models, currently applied to forecast demand amounts and prices. It describes limits of time-series models and fundamental ones in case of hourly forecasting an irregular demand schedule of the electricity market entity. The features of electricity trading at WEM are carefully analysed. Factors that influence on irregularity of demand schedule of the metallurgical plant are shown. The article proposes method for the qualitative forecast of market price ratios as a tool to reduce a dependence on the accuracy of forecasting an irregular schedule of demand. It describes the differences between the offered method and the similar ones considered in research studies and scholarly works. The correlation between price ratios and relaxation in the requirements for the forecast accuracy of the electric power consumption is analysed. The efficiency function of forecast method is derived. The article puts an increased focus on description of the mathematical model based on the method of qualitative forecast. It shows main model parameters and restrictions the electricity market imposes on them. The model prototype is described as a programme module. Methods to assess an effectiveness of the proposed forecast model are examined. The positive test results of the model using JSC «Volzhsky Pipe Plant» data are given. A conclusion is drawn concerning the possibility to decrease dependence on the forecast accuracy of irregular schedule of entity’s demand at WEM. The effective trading tool has been found for the entities of irregular demand schedule at WEM. The tool application allows minimizing cost

  13. A Novel Nonlinear Combined Forecasting System for Short-Term Load Forecasting

    Directory of Open Access Journals (Sweden)

    Chengshi Tian

    2018-03-01

    Full Text Available Short-term load forecasting plays an indispensable role in electric power systems, which is not only an extremely challenging task but also a concerning issue for all society due to complex nonlinearity characteristics. However, most previous combined forecasting models were based on optimizing weight coefficients to develop a linear combined forecasting model, while ignoring that the linear combined model only considers the contribution of the linear terms to improving the model’s performance, which will lead to poor forecasting results because of the significance of the neglected and potential nonlinear terms. In this paper, a novel nonlinear combined forecasting system, which consists of three modules (improved data pre-processing module, forecasting module and the evaluation module is developed for short-term load forecasting. Different from the simple data pre-processing of most previous studies, the improved data pre-processing module based on longitudinal data selection is successfully developed in this system, which further improves the effectiveness of data pre-processing and then enhances the final forecasting performance. Furthermore, the modified support vector machine is developed to integrate all the individual predictors and obtain the final prediction, which successfully overcomes the upper drawbacks of the linear combined model. Moreover, the evaluation module is incorporated to perform a scientific evaluation for the developed system. The half-hourly electrical load data from New South Wales are employed to verify the effectiveness of the developed forecasting system, and the results reveal that the developed nonlinear forecasting system can be employed in the dispatching and planning for smart grids.

  14. Project in fiscal 1988 for research and development of basic technologies in next generation industries. Research and development of superconducting materials and superconducting elements (Achievement report on forecast and research of superconducting element technologies); 1988 nendo chodendo soshi gijutsu yosoku kenkyu seika hokokusho

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1989-03-01

    With an objective to perform survey and forecast on the future of superconducting elements, collection of latest technological information and analyses of technological trends were carried out by members of the Technology Forecast and Research Committee. This paper summarizes the achievements therein. It was discovered that the Josephson element using an Al{sub 2}O{sub 3} barrier and an Nb electrode shows excellent characteristics with very good reproducibility. Trial fabrication of a four-bit micro processor was recently executed successfully by the SQUID gate using the above element. On the other hand, application of devices using high-temperature superconductors has not come out with an achievement. Although a large number of achievements have been released on mono-crystalline thin films that show good characteristics, development of substrates and barrier materials is still needed for device configuration. The method for manufacturing metal-based superconducting films has been established nearly completely as an elementary technology to develop the superconducting elements. However, making thinner the high-temperature superconducting films having been discovered recently is encountering a number of inherent problems, whereas the present stage is such that experimental discussions are being made. The process technologies, simulation, and evaluation technologies are basically the same as those for the metallic systems even for the oxide superconduction. (NEDO)

  15. Short-term ensemble radar rainfall forecasts for hydrological applications

    Science.gov (United States)

    Codo de Oliveira, M.; Rico-Ramirez, M. A.

    2016-12-01

    Flooding is a very common natural disaster around the world, putting local population and economy at risk. Forecasting floods several hours ahead and issuing warnings are of main importance to permit proper response in emergency situations. However, it is important to know the uncertainties related to the rainfall forecasting in order to produce more reliable forecasts. Nowcasting models (short-term rainfall forecasts) are able to produce high spatial and temporal resolution predictions that are useful in hydrological applications. Nonetheless, they are subject to uncertainties mainly due to the nowcasting model used, errors in radar rainfall estimation, temporal development of the velocity field and to the fact that precipitation processes such as growth and decay are not taken into account. In this study an ensemble generation scheme using rain gauge data as a reference to estimate radars errors is used to produce forecasts with up to 3h lead-time. The ensembles try to assess in a realistic way the residual uncertainties that remain even after correction algorithms are applied in the radar data. The ensembles produced are compered to a stochastic ensemble generator. Furthermore, the rainfall forecast output was used as an input in a hydrodynamic sewer network model and also in hydrological model for catchments of different sizes in north England. A comparative analysis was carried of how was carried out to assess how the radar uncertainties propagate into these models. The first named author is grateful to CAPES - Ciencia sem Fronteiras for funding this PhD research.

  16. ASSESSMENT OF QUALITY OF INNOVATIVE TECHNOLOGIES

    OpenAIRE

    Larisa Alexejevna Ismagilova; Nadegda Aleksandrovna Sukhova

    2016-01-01

    We consider the topical issue of implementation of innovative technologies in the aircraft engine building industry. In this industry, products with high reliability requirements are developed and mass-produced. These products combine the latest achievements of science and technology. To make a decision on implementation of innovative technologies, a comprehensive assessment is carried out. It affects the efficiency of the innovations realization. In connection with this, the assessment of qu...

  17. Institutionalising health technology assessment: establishing the Medical Technology Assessment Board in India.

    Science.gov (United States)

    Downey, Laura E; Mehndiratta, Abha; Grover, Ashoo; Gauba, Vijay; Sheikh, Kabir; Prinja, Shankar; Singh, Ravinder; Cluzeau, Francoise A; Dabak, Saudamini; Teerawattananon, Yot; Kumar, Sanjiv; Swaminathan, Soumya

    2017-01-01

    India is at crossroads with a commitment by the government to universal health coverage (UHC), driving efficiency and tackling waste across the public healthcare sector. Health technology assessment (HTA) is an important policy reform that can assist policy-makers to tackle inequities and inefficiencies by improving the way in which health resources are allocated towards cost-effective, appropriate and feasible interventions. The equitable and efficient distribution of health budget resources, as well as timely uptake of good value technologies, are critical to strengthen the Indian healthcare system. The government of India is set to establish a Medical Technology Assessment Board to evaluate existing and new health technologies in India, assist choices between comparable technologies for adoption by the healthcare system and improve the way in which priorities for health are set. This initiative aims to introduce a more transparent, inclusive, fair and evidence-based process by which decisions regarding the allocation of health resources are made in India towards the ultimate goal of UHC. In this analysis article, we report on plans and progress of the government of India for the institutionalisation of HTA in the country. Where India is home to one-sixth of the global population, improving the health services that the population receives will have a resounding impact not only for India but also for global health.

  18. Energy demand forecasting method based on international statistical data

    International Nuclear Information System (INIS)

    Glanc, Z.; Kerner, A.

    1997-01-01

    Poland is in a transition phase from a centrally planned to a market economy; data collected under former economic conditions do not reflect a market economy. Final energy demand forecasts are based on the assumption that the economic transformation in Poland will gradually lead the Polish economy, technologies and modes of energy use, to the same conditions as mature market economy countries. The starting point has a significant influence on the future energy demand and supply structure: final energy consumption per capita in 1992 was almost half the average of OECD countries; energy intensity, based on Purchasing Power Parities (PPP) and referred to GDP, is more than 3 times higher in Poland. A method of final energy demand forecasting based on regression analysis is described in this paper. The input data are: output of macroeconomic and population growth forecast; time series 1970-1992 of OECD countries concerning both macroeconomic characteristics and energy consumption; and energy balance of Poland for the base year of the forecast horizon. (author). 1 ref., 19 figs, 4 tabs

  19. Energy demand forecasting method based on international statistical data

    Energy Technology Data Exchange (ETDEWEB)

    Glanc, Z; Kerner, A [Energy Information Centre, Warsaw (Poland)

    1997-09-01

    Poland is in a transition phase from a centrally planned to a market economy; data collected under former economic conditions do not reflect a market economy. Final energy demand forecasts are based on the assumption that the economic transformation in Poland will gradually lead the Polish economy, technologies and modes of energy use, to the same conditions as mature market economy countries. The starting point has a significant influence on the future energy demand and supply structure: final energy consumption per capita in 1992 was almost half the average of OECD countries; energy intensity, based on Purchasing Power Parities (PPP) and referred to GDP, is more than 3 times higher in Poland. A method of final energy demand forecasting based on regression analysis is described in this paper. The input data are: output of macroeconomic and population growth forecast; time series 1970-1992 of OECD countries concerning both macroeconomic characteristics and energy consumption; and energy balance of Poland for the base year of the forecast horizon. (author). 1 ref., 19 figs, 4 tabs.

  20. Characterizing emerging industrial technologies in energy models

    Energy Technology Data Exchange (ETDEWEB)

    Laitner, John A. (Skip); Worrell, Ernst; Galitsky, Christina; Hanson, Donald A.

    2003-07-29

    Conservation supply curves are a common tool in economic analysis. As such, they provide an important opportunity to include a non-linear representation of technology and technological change in economy-wide models. Because supply curves are closely related to production isoquants, we explore the possibility of using bottom-up technology assessments to inform top-down representations of energy models of the U.S. economy. Based on a recent report by LBNL and ACEEE on emerging industrial technologies within the United States, we have constructed a supply curve for 54 such technologies for the year 2015. Each of the selected technologies has been assessed with respect to energy efficiency characteristics, likely energy savings by 2015, economics, and environmental performance, as well as needs for further development or implementation of the technology. The technical potential for primary energy savings of the 54 identified technologies is equal to 3.54 Quads, or 8.4 percent of the assume d2015 industrial energy consumption. Based on the supply curve, assuming a discount rate of 15 percent and 2015 prices as forecasted in the Annual Energy Outlook2002, we estimate the economic potential to be 2.66 Quads - or 6.3 percent of the assumed forecast consumption for 2015. In addition, we further estimate how much these industrial technologies might contribute to standard reference case projections, and how much additional energy savings might be available assuming a different mix of policies and incentives. Finally, we review the prospects for integrating the findings of this and similar studies into standard economic models. Although further work needs to be completed to provide the necessary link between supply curves and production isoquants, it is hoped that this link will be a useful starting point for discussion with developers of energy-economic models.

  1. Forecasting The Onset Of The East African Rains

    Science.gov (United States)

    MacLeod, D.; Palmer, T.

    2017-12-01

    The timing of the rainy seasons is critical for East Africa, where many livelihoods depend on rain-fed agriculture. The exact onset date of the rains varies from year to year and a delayed start has significant implications for food security. Early warning of anomalous onset can help mitigate risks by informing farmer decisions on crop choice and timing of planting. Onset forecasts may also pre-warn governments and NGOs of upcoming need for financial support and humanitarian intervention. Here we assess the potential to forecast the onset of both the short and long rains over East Africa at subseasonal to seasonal timescales. Based on operational reforecasts from ECMWF, we will demonstrate skilful prediction of onset anomalies. An investigation to determine potential sources of this forecast skill will also be presented. This work has been carried out as part of the project ForPAc: "Towards forecast-based preparedness action".

  2. Magnetogram Forecast: An All-Clear Space Weather Forecasting System

    Science.gov (United States)

    Barghouty, Nasser; Falconer, David

    2015-01-01

    Solar flares and coronal mass ejections (CMEs) are the drivers of severe space weather. Forecasting the probability of their occurrence is critical in improving space weather forecasts. The National Oceanic and Atmospheric Administration (NOAA) currently uses the McIntosh active region category system, in which each active region on the disk is assigned to one of 60 categories, and uses the historical flare rates of that category to make an initial forecast that can then be adjusted by the NOAA forecaster. Flares and CMEs are caused by the sudden release of energy from the coronal magnetic field by magnetic reconnection. It is believed that the rate of flare and CME occurrence in an active region is correlated with the free energy of an active region. While the free energy cannot be measured directly with present observations, proxies of the free energy can instead be used to characterize the relative free energy of an active region. The Magnetogram Forecast (MAG4) (output is available at the Community Coordinated Modeling Center) was conceived and designed to be a databased, all-clear forecasting system to support the operational goals of NASA's Space Radiation Analysis Group. The MAG4 system automatically downloads nearreal- time line-of-sight Helioseismic and Magnetic Imager (HMI) magnetograms on the Solar Dynamics Observatory (SDO) satellite, identifies active regions on the solar disk, measures a free-energy proxy, and then applies forecasting curves to convert the free-energy proxy into predicted event rates for X-class flares, M- and X-class flares, CMEs, fast CMEs, and solar energetic particle events (SPEs). The forecast curves themselves are derived from a sample of 40,000 magnetograms from 1,300 active region samples, observed by the Solar and Heliospheric Observatory Michelson Doppler Imager. Figure 1 is an example of MAG4 visual output

  3. Communicating weather forecast uncertainty: Do individual differences matter?

    Science.gov (United States)

    Grounds, Margaret A; Joslyn, Susan L

    2018-03-01

    Research suggests that people make better weather-related decisions when they are given numeric probabilities for critical outcomes (Joslyn & Leclerc, 2012, 2013). However, it is unclear whether all users can take advantage of probabilistic forecasts to the same extent. The research reported here assessed key cognitive and demographic factors to determine their relationship to the use of probabilistic forecasts to improve decision quality. In two studies, participants decided between spending resources to prevent icy conditions on roadways or risk a larger penalty when freezing temperatures occurred. Several forecast formats were tested, including a control condition with the night-time low temperature alone and experimental conditions that also included the probability of freezing and advice based on expected value. All but those with extremely low numeracy scores made better decisions with probabilistic forecasts. Importantly, no groups made worse decisions when probabilities were included. Moreover, numeracy was the best predictor of decision quality, regardless of forecast format, suggesting that the advantage may extend beyond understanding the forecast to general decision strategy issues. This research adds to a growing body of evidence that numerical uncertainty estimates may be an effective way to communicate weather danger to general public end users. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  4. Medium Range Forecasts Representation (and Long Range Forecasts?)

    Science.gov (United States)

    Vincendon, J.-C.

    2009-09-01

    The progress of the numerical forecasts urges us to interest us in more and more distant ranges. We thus supply more and more forecasts with term of some days. Nevertheless, precautions of use are necessary to give the most reliable and the most relevant possible information. Available in a TV bulletin or on quite other support (Internet, mobile phone), the interpretation and the representation of a medium range forecast (5 - 15 days) must be different from those of a short range forecast. Indeed, the "foresee-ability” of a meteorological phenomenon decreases gradually in the course of the ranges, it decreases all the more quickly that the phenomenon is of small scale. So, at the end of some days, the probability character of a forecast becomes very widely dominating. That is why in Meteo-France the forecasts of D+4 to D+7 are accompanied with a confidence index since around ten years. It is a figure between 1 and 5: the more we approach 5, the more the confidence in the supplied forecast is good. In the practice, an indication is supplied for period D+4 / D+5, the other one for period D+6 / D+7, every day being able to benefit from a different forecast, that is be represented in a independent way. We thus supply a global tendency over 24 hours with less and less precise symbols as the range goes away. Concrete examples will be presented. From now on two years, we also publish forecasts to D+8 / J+9, accompanied with a sign of confidence (" good reliability " or " to confirm "). These two days are grouped together on a single map because for us, the described tendency to this term is relevant on a duration about 48 hours with a spatial scale slightly superior to the synoptic scale. So, we avoid producing more than two zones of types of weather over France and we content with giving an evolution for the temperatures (still, in increase or in decline). Newspapers began to publish this information, it should soon be the case of televisions. It is particularly

  5. The multi temporal/multi-model approach to predictive uncertainty assessment in real-time flood forecasting

    Science.gov (United States)

    Barbetta, Silvia; Coccia, Gabriele; Moramarco, Tommaso; Brocca, Luca; Todini, Ezio

    2017-08-01

    This work extends the multi-temporal approach of the Model Conditional Processor (MCP-MT) to the multi-model case and to the four Truncated Normal Distributions (TNDs) approach, demonstrating the improvement on the single-temporal one. The study is framed in the context of probabilistic Bayesian decision-making that is appropriate to take rational decisions on uncertain future outcomes. As opposed to the direct use of deterministic forecasts, the probabilistic forecast identifies a predictive probability density function that represents a fundamental knowledge on future occurrences. The added value of MCP-MT is the identification of the probability that a critical situation will happen within the forecast lead-time and when, more likely, it will occur. MCP-MT is thoroughly tested for both single-model and multi-model configurations at a gauged site on the Tiber River, central Italy. The stages forecasted by two operative deterministic models, STAFOM-RCM and MISDc, are considered for the study. The dataset used for the analysis consists of hourly data from 34 flood events selected on a time series of six years. MCP-MT improves over the original models' forecasts: the peak overestimation and the rising limb delayed forecast, characterizing MISDc and STAFOM-RCM respectively, are significantly mitigated, with a reduced mean error on peak stage from 45 to 5 cm and an increased coefficient of persistence from 0.53 up to 0.75. The results show that MCP-MT outperforms the single-temporal approach and is potentially useful for supporting decision-making because the exceedance probability of hydrometric thresholds within a forecast horizon and the most probable flooding time can be estimated.

  6. The strategy of professional forecasting

    DEFF Research Database (Denmark)

    Ottaviani, Marco; Sørensen, Peter Norman

    2006-01-01

    We develop and compare two theories of professional forecasters’ strategic behavior. The first theory, reputational cheap talk, posits that forecasters endeavor to convince the market that they are well informed. The market evaluates their forecasting talent on the basis of the forecasts...... and the realized state. If the market expects forecasters to report their posterior expectations honestly, then forecasts are shaded toward the prior mean. With correct market expectations, equilibrium forecasts are imprecise but not shaded. The second theory posits that forecasters compete in a forecasting...... contest with pre-specified rules. In a winner-take-all contest, equilibrium forecasts are excessively differentiated...

  7. Evaluating the Effectiveness of DART® Buoy Networks Based on Forecast Accuracy

    Science.gov (United States)

    Percival, Donald B.; Denbo, Donald W.; Gica, Edison; Huang, Paul Y.; Mofjeld, Harold O.; Spillane, Michael C.; Titov, Vasily V.

    2018-03-01

    A performance measure for a DART® tsunami buoy network has been developed. DART® buoys are used to detect tsunamis, but the full potential of the data they collect is realized through accurate forecasts of inundations caused by the tsunamis. The performance measure assesses how well the network achieves its full potential through a statistical analysis of simulated forecasts of wave amplitudes outside an impact site and a consideration of how much the forecasts are degraded in accuracy when one or more buoys are inoperative. The analysis uses simulated tsunami amplitude time series collected at each buoy from selected source segments in the Short-term Inundation Forecast for Tsunamis database and involves a set for 1000 forecasts for each buoy/segment pair at sites just offshore of selected impact communities. Random error-producing scatter in the time series is induced by uncertainties in the source location, addition of real oceanic noise, and imperfect tidal removal. Comparison with an error-free standard leads to root-mean-square errors (RMSEs) for DART® buoys located near a subduction zone. The RMSEs indicate which buoy provides the best forecast (lowest RMSE) for sections of the zone, under a warning-time constraint for the forecasts of 3 h. The analysis also shows how the forecasts are degraded (larger minimum RMSE among the remaining buoys) when one or more buoys become inoperative. The RMSEs provide a way to assess array augmentation or redesign such as moving buoys to more optimal locations. Examples are shown for buoys off the Aleutian Islands and off the West Coast of South America for impact sites at Hilo HI and along the US West Coast (Crescent City CA and Port San Luis CA, USA). A simple measure (coded green, yellow or red) of the current status of the network's ability to deliver accurate forecasts is proposed to flag the urgency of buoy repair.

  8. Evaluating the Effectiveness of DART® Buoy Networks Based on Forecast Accuracy

    Science.gov (United States)

    Percival, Donald B.; Denbo, Donald W.; Gica, Edison; Huang, Paul Y.; Mofjeld, Harold O.; Spillane, Michael C.; Titov, Vasily V.

    2018-04-01

    A performance measure for a DART® tsunami buoy network has been developed. DART® buoys are used to detect tsunamis, but the full potential of the data they collect is realized through accurate forecasts of inundations caused by the tsunamis. The performance measure assesses how well the network achieves its full potential through a statistical analysis of simulated forecasts of wave amplitudes outside an impact site and a consideration of how much the forecasts are degraded in accuracy when one or more buoys are inoperative. The analysis uses simulated tsunami amplitude time series collected at each buoy from selected source segments in the Short-term Inundation Forecast for Tsunamis database and involves a set for 1000 forecasts for each buoy/segment pair at sites just offshore of selected impact communities. Random error-producing scatter in the time series is induced by uncertainties in the source location, addition of real oceanic noise, and imperfect tidal removal. Comparison with an error-free standard leads to root-mean-square errors (RMSEs) for DART® buoys located near a subduction zone. The RMSEs indicate which buoy provides the best forecast (lowest RMSE) for sections of the zone, under a warning-time constraint for the forecasts of 3 h. The analysis also shows how the forecasts are degraded (larger minimum RMSE among the remaining buoys) when one or more buoys become inoperative. The RMSEs provide a way to assess array augmentation or redesign such as moving buoys to more optimal locations. Examples are shown for buoys off the Aleutian Islands and off the West Coast of South America for impact sites at Hilo HI and along the US West Coast (Crescent City CA and Port San Luis CA, USA). A simple measure (coded green, yellow or red) of the current status of the network's ability to deliver accurate forecasts is proposed to flag the urgency of buoy repair.

  9. Using Seasonal Forecasting Data for Vessel Routing

    Science.gov (United States)

    Bell, Ray; Kirtman, Ben

    2017-04-01

    We present an assessment of seasonal forecasting of surface wind speed, significant wave height and ocean surface current speed in the North Pacific for potential use of vessel routing from Singapore to San Diego. WaveWatchIII is forced with surface winds and ocean surface currents from the Community Climate System Model 4 (CCSM4) retrospective forecasts for the period of 1982-2015. Several lead time forecasts are used from zero months to six months resulting in 2,720 model years, ensuring the findings from this study are robust. July surface wind speed and significant wave height can be skillfully forecast with a one month lead time, with the western North Pacific being the most predictable region. Beyond May initial conditions (lead time of two months) the El Niño Southern Oscillation (ENSO) Spring predictability barrier limits skill of significant wave height but there is skill for surface wind speed with January initial conditions (lead time of six months). In a separate study of vessel routing between Norfolk, Virginia and Gibraltar we demonstrate the benefit of a multimodel approach using the North American Multimodel Ensemble (NMME). In collaboration with Charles River Analytics an all-encompassing forecast is presented by using machine learning on the various ensembles which can be using used for industry applications.

  10. Are Forecast Updates Progressive?

    NARCIS (Netherlands)

    C-L. Chang (Chia-Lin); Ph.H.B.F. Franses (Philip Hans); M.J. McAleer (Michael)

    2010-01-01

    textabstractMacro-economic forecasts typically involve both a model component, which is replicable, as well as intuition, which is non-replicable. Intuition is expert knowledge possessed by a forecaster. If forecast updates are progressive, forecast updates should become more accurate, on average,

  11. Linking seasonal climate forecasts with crop models in Iberian Peninsula

    Science.gov (United States)

    Capa, Mirian; Ines, Amor; Baethgen, Walter; Rodriguez-Fonseca, Belen; Han, Eunjin; Ruiz-Ramos, Margarita

    2015-04-01

    Translating seasonal climate forecasts into agricultural production forecasts could help to establish early warning systems and to design crop management adaptation strategies that take advantage of favorable conditions or reduce the effect of adverse conditions. In this study, we use seasonal rainfall forecasts and crop models to improve predictability of wheat yield in the Iberian Peninsula (IP). Additionally, we estimate economic margins and production risks associated with extreme scenarios of seasonal rainfall forecast. This study evaluates two methods for disaggregating seasonal climate forecasts into daily weather data: 1) a stochastic weather generator (CondWG), and 2) a forecast tercile resampler (FResampler). Both methods were used to generate 100 (with FResampler) and 110 (with CondWG) weather series/sequences for three scenarios of seasonal rainfall forecasts. Simulated wheat yield is computed with the crop model CERES-wheat (Ritchie and Otter, 1985), which is included in Decision Support System for Agrotechnology Transfer (DSSAT v.4.5, Hoogenboom et al., 2010). Simulations were run at two locations in northeastern Spain where the crop model was calibrated and validated with independent field data. Once simulated yields were obtained, an assessment of farmer's gross margin for different seasonal climate forecasts was accomplished to estimate production risks under different climate scenarios. This methodology allows farmers to assess the benefits and risks of a seasonal weather forecast in IP prior to the crop growing season. The results of this study may have important implications on both, public (agricultural planning) and private (decision support to farmers, insurance companies) sectors. Acknowledgements Research by M. Capa-Morocho has been partly supported by a PICATA predoctoral fellowship of the Moncloa Campus of International Excellence (UCM-UPM) and MULCLIVAR project (CGL2012-38923-C02-02) References Hoogenboom, G. et al., 2010. The Decision

  12. Three-dimensional visualization of ensemble weather forecasts – Part 1: The visualization tool Met.3D (version 1.0

    Directory of Open Access Journals (Sweden)

    M. Rautenhaus

    2015-07-01

    Full Text Available We present "Met.3D", a new open-source tool for the interactive three-dimensional (3-D visualization of numerical ensemble weather predictions. The tool has been developed to support weather forecasting during aircraft-based atmospheric field campaigns; however, it is applicable to further forecasting, research and teaching activities. Our work approaches challenging topics related to the visual analysis of numerical atmospheric model output – 3-D visualization, ensemble visualization and how both can be used in a meaningful way suited to weather forecasting. Met.3D builds a bridge from proven 2-D visualization methods commonly used in meteorology to 3-D visualization by combining both visualization types in a 3-D context. We address the issue of spatial perception in the 3-D view and present approaches to using the ensemble to allow the user to assess forecast uncertainty. Interactivity is key to our approach. Met.3D uses modern graphics technology to achieve interactive visualization on standard consumer hardware. The tool supports forecast data from the European Centre for Medium Range Weather Forecasts (ECMWF and can operate directly on ECMWF hybrid sigma-pressure level grids. We describe the employed visualization algorithms, and analyse the impact of the ECMWF grid topology on computing 3-D ensemble statistical quantities. Our techniques are demonstrated with examples from the T-NAWDEX-Falcon 2012 (THORPEX – North Atlantic Waveguide and Downstream Impact Experiment campaign.

  13. Technology Assessment Need: Review on Attractiveness and Competitiveness

    Science.gov (United States)

    Salwa Sait, Siti; Merlinda Muharam, Farrah; Chin, Thoo Ai; Sulaiman, Zuraidah

    2017-06-01

    Technology assessment is crucial in managing technology for the purpose of technology exploitation. With business environment continuously changing, firms have to address this issue critically as technology is considered one of the important elements to evaluate performance and gain competitive advantage. Missteps in deciding the best technology to be developed, employed or maintained would cost the firm overall value. To fulfil the need of finding the appropriate scale to assess suitable technology, this paper summarizes that technology assessment (TA) should cover two main aspects, namely technology attractiveness and competitiveness. These components are seen capable to link the scale suggested towards evaluation of financial and non-financial performance towards competitive advantage.

  14. The Rise of Complexity in Flood Forecasting: Opportunities, Challenges and Tradeoffs

    Science.gov (United States)

    Wood, A. W.; Clark, M. P.; Nijssen, B.

    2017-12-01

    Operational flood forecasting is currently undergoing a major transformation. Most national flood forecasting services have relied for decades on lumped, highly calibrated conceptual hydrological models running on local office computing resources, providing deterministic streamflow predictions at gauged river locations that are important to stakeholders and emergency managers. A variety of recent technological advances now make it possible to run complex, high-to-hyper-resolution models for operational hydrologic prediction over large domains, and the US National Weather Service is now attempting to use hyper-resolution models to create new forecast services and products. Yet other `increased-complexity' forecasting strategies also exist that pursue different tradeoffs between model complexity (i.e., spatial resolution, physics) and streamflow forecast system objectives. There is currently a pressing need for a greater understanding in the hydrology community of the opportunities, challenges and tradeoffs associated with these different forecasting approaches, and for a greater participation by the hydrology community in evaluating, guiding and implementing these approaches. Intermediate-resolution forecast systems, for instance, use distributed land surface model (LSM) physics but retain the agility to deploy ensemble methods (including hydrologic data assimilation and hindcast-based post-processing). Fully coupled numerical weather prediction (NWP) systems, another example, use still coarser LSMs to produce ensemble streamflow predictions either at the model scale or after sub-grid scale runoff routing. Based on the direct experience of the authors and colleagues in research and operational forecasting, this presentation describes examples of different streamflow forecast paradigms, from the traditional to the recent hyper-resolution, to illustrate the range of choices facing forecast system developers. We also discuss the degree to which the strengths and

  15. Optimal operation and forecasting policy for pump storage plants in day-ahead markets

    International Nuclear Information System (INIS)

    Muche, Thomas

    2014-01-01

    Highlights: • We investigate unit commitment deploying stochastic and deterministic approaches. • We consider day-ahead markets, its forecast and weekly price based unit commitment. • Stochastic and deterministic unit commitment are identical for the first planning day. • Unit commitment and bidding policy can be based on the deterministic approach. • Robust forecasting models should be estimated based on the whole planning horizon. - Abstract: Pump storage plants are an important electricity storage technology at present. Investments in this technology are expected to increase. The necessary investment valuation often includes expected cash flows from future price-based unit commitment policies. A price-based unit commitment policy has to consider market price uncertainty and the information revealing nature of electricity markets. For this environment stochastic programming models are suggested to derive the optimal unit commitment policy. For the considered day-ahead price electricity market stochastic and deterministic unit commitment policies are comparable suggesting an application of easier implementable deterministic models. In order to identify suitable unit commitment and forecasting policies, deterministic unit commitment models are applied to actual day-ahead electricity prices of a whole year. As a result, a robust forecasting model should consider the unit commitment planning period. This robust forecasting models result in expected cash flows similar to realized ones allowing a reliable investment valuation

  16. What influences the choice of assessment methods in health technology assessments? Statistical analysis of international health technology assessments from 1989 to 2002.

    Science.gov (United States)

    Draborg, Eva; Andersen, Christian Kronborg

    2006-01-01

    Health technology assessment (HTA) has been used as input in decision making worldwide for more than 25 years. However, no uniform definition of HTA or agreement on assessment methods exists, leaving open the question of what influences the choice of assessment methods in HTAs. The objective of this study is to analyze statistically a possible relationship between methods of assessment used in practical HTAs, type of assessed technology, type of assessors, and year of publication. A sample of 433 HTAs published by eleven leading institutions or agencies in nine countries was reviewed and analyzed by multiple logistic regression. The study shows that outsourcing of HTA reports to external partners is associated with a higher likelihood of using assessment methods, such as meta-analysis, surveys, economic evaluations, and randomized controlled trials; and with a lower likelihood of using assessment methods, such as literature reviews and "other methods". The year of publication was statistically related to the inclusion of economic evaluations and shows a decreasing likelihood during the year span. The type of assessed technology was related to economic evaluations with a decreasing likelihood, to surveys, and to "other methods" with a decreasing likelihood when pharmaceuticals were the assessed type of technology. During the period from 1989 to 2002, no major developments in assessment methods used in practical HTAs were shown statistically in a sample of 433 HTAs worldwide. Outsourcing to external assessors has a statistically significant influence on choice of assessment methods.

  17. PACS/IMAC technology assessment

    OpenAIRE

    Schilling, Ronald B.

    1997-01-01

    According to Peter Ogle of Digital Imaging (San Francisco, CA), “Radiologists should help identify common values for the use of information technology in medicine.” Achieving a set of common values often requires a framework for organizing the thought process involved. That is the focus of this article in addressing the subject of picture archiving and communication system (PACS) technology assessment.

  18. The Papers Printing Quality Complex Assessment Algorithm Development Taking into Account the Composition and Production Technological Features

    Science.gov (United States)

    Babakhanova, Kh A.; Varepo, L. G.; Nagornova, I. V.; Babluyk, E. B.; Kondratov, A. P.

    2018-04-01

    Paper is one of the printing system key components causing the high-quality printed products output. Providing the printing companies with the specified printing properties paper, while simultaneously increasing the paper products range and volume by means of the forecasting methods application and evaluation during the production process, is certainly a relevant problem. The paper presents the printing quality control algorithm taking into consideration the paper printing properties quality assessment depending on the manufacture technological features and composition variation. The information system including raw material and paper properties data and making possible pulp and paper enterprises to select paper composition optimal formulation is proposed taking into account the printing process procedure peculiarities of the paper manufacturing with specified printing properties.

  19. Deterministic and heuristic models of forecasting spare parts demand

    Directory of Open Access Journals (Sweden)

    Ivan S. Milojević

    2012-04-01

    of preventive maintenance, the number of assets on which the preventive maintenance procedures are performed and the technology of maintaining procedures are known, then the range and the quantity of spare parts needed to perform these procedures are also known. Heuristic forecasting is related to the experts. Armed forces use it for the assessment of combat situation, taking into account the opponent's and its own action tactics, forecasting enemy's intentions, analyzing the plan of operations, making decision for the plan of action, etc. In this case, relatively unregulated systems are those in which there is no data about the observed phenomenon and its development in the past. In addition to the fact that the above data does not exist, there is a need for spare parts demand forecasts for the purpose of decision making and inventory management. This primarily relates to the period of transition from an unregulated to a regulated system. In this case, forecasting has a limited range. No forecasting can be done for a longer period; the forecasting is reduced to the next relevant interval, i.e. to the interval relevant for the system. The application of another, relatively simple model which uses computer techniques has no particular limitations, but for that reason its results are time-limited; results are obtained only for the subsequent relevant period. The results of this model have a very limited range in planning. This model is applicable mainly in unregulated systems. It is suitable for so-called condition 'clearing'. After one or two closed cycles, a situation is brought to order, but then much more sensitive models are needed.

  20. Forecasting the Seasonal Timing of Maine's Lobster Fishery

    Directory of Open Access Journals (Sweden)

    Katherine E. Mills

    2017-11-01

    Full Text Available The fishery for American lobster is currently the highest-valued commercial fishery in the United States, worth over US$620 million in dockside value in 2015. During a marine heat wave in 2012, the fishery was disrupted by the early warming of spring ocean temperatures and subsequent influx of lobster landings. This situation resulted in a price collapse, as the supply chain was not prepared for the early and abundant landings of lobsters. Motivated by this series of events, we have developed a forecast of when the Maine (USA lobster fishery will shift into its high volume summer landings period. The forecast uses a regression approach to relate spring ocean temperatures derived from four NERACOOS buoys along the coast of Maine to the start day of the high landings period of the fishery. Tested against conditions in past years, the forecast is able to predict the start day to within 1 week of the actual start, and the forecast can be issued 3–4 months prior to the onset of the high-landings period, providing valuable lead-time for the fishery and its associated supply chain to prepare for the upcoming season. Forecast results are conveyed in a probabilistic manner and are updated weekly over a 6-week forecasting period so that users can assess the certainty and consistency of the forecast and factor the uncertainty into their use of the information in a given year. By focusing on the timing of events, this type of seasonal forecast provides climate-relevant information to users at time scales that are meaningful for operational decisions. As climate change alters seasonal phenology and reduces the reliability of past experience as a guide for future expectations, this type of forecast can enable fishing industry participants to better adjust to and prepare for operating in the context of climate change.

  1. Relating Tropical Cyclone Track Forecast Error Distributions with Measurements of Forecast Uncertainty

    Science.gov (United States)

    2016-03-01

    CYCLONE TRACK FORECAST ERROR DISTRIBUTIONS WITH MEASUREMENTS OF FORECAST UNCERTAINTY by Nicholas M. Chisler March 2016 Thesis Advisor...March 2016 3. REPORT TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE RELATING TROPICAL CYCLONE TRACK FORECAST ERROR DISTRIBUTIONS...WITH MEASUREMENTS OF FORECAST UNCERTAINTY 5. FUNDING NUMBERS 6. AUTHOR(S) Nicholas M. Chisler 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES

  2. Forecasting urban water demand: A meta-regression analysis.

    Science.gov (United States)

    Sebri, Maamar

    2016-12-01

    Water managers and planners require accurate water demand forecasts over the short-, medium- and long-term for many purposes. These range from assessing water supply needs over spatial and temporal patterns to optimizing future investments and planning future allocations across competing sectors. This study surveys the empirical literature on the urban water demand forecasting using the meta-analytical approach. Specifically, using more than 600 estimates, a meta-regression analysis is conducted to identify explanations of cross-studies variation in accuracy of urban water demand forecasting. Our study finds that accuracy depends significantly on study characteristics, including demand periodicity, modeling method, forecasting horizon, model specification and sample size. The meta-regression results remain robust to different estimators employed as well as to a series of sensitivity checks performed. The importance of these findings lies in the conclusions and implications drawn out for regulators and policymakers and for academics alike. Copyright © 2016. Published by Elsevier Ltd.

  3. Grey Forecast Rainfall with Flow Updating Algorithm for Real-Time Flood Forecasting

    Directory of Open Access Journals (Sweden)

    Jui-Yi Ho

    2015-04-01

    Full Text Available The dynamic relationship between watershed characteristics and rainfall-runoff has been widely studied in recent decades. Since watershed rainfall-runoff is a non-stationary process, most deterministic flood forecasting approaches are ineffective without the assistance of adaptive algorithms. The purpose of this paper is to propose an effective flow forecasting system that integrates a rainfall forecasting model, watershed runoff model, and real-time updating algorithm. This study adopted a grey rainfall forecasting technique, based on existing hourly rainfall data. A geomorphology-based runoff model can be used for simulating impacts of the changing geo-climatic conditions on the hydrologic response of unsteady and non-linear watershed system, and flow updating algorithm were combined to estimate watershed runoff according to measured flow data. The proposed flood forecasting system was applied to three watersheds; one in the United States and two in Northern Taiwan. Four sets of rainfall-runoff simulations were performed to test the accuracy of the proposed flow forecasting technique. The results indicated that the forecast and observed hydrographs are in good agreement for all three watersheds. The proposed flow forecasting system could assist authorities in minimizing loss of life and property during flood events.

  4. Forecast of useful energy for the TIMES-Norway model

    International Nuclear Information System (INIS)

    Rosenberg, Eva

    2012-01-01

    A regional forecast of useful energy demand in seven Norwegian regions is calculated based on an earlier work with a national forecast. This forecast will be input to the energy system model TIMES-Norway and analyses will result in forecasts of energy use of different energy carriers with varying external conditions (not included in this report). The forecast presented here describes the methodology used and the resulting forecast of useful energy. lt is based on information of the long-term development of the economy by the Ministry of Finance, projections of population growths from Statistics Norway and several other studies. The definition of a forecast of useful energy demand is not absolute, but depends on the purpose. One has to be careful not to include parts that are a part of the energy system model, such as energy efficiency measures. In the forecast presented here the influence of new building regulations and the prohibition of production of incandescent light bulbs in EU etc. are included. Other energy efficiency measures such as energy management, heat pumps, tightening of leaks etc. are modelled as technologies to invest in and are included in the TIMES-Norway model. The elasticity between different energy carriers are handled by the TIMES-Norway model and some elasticity is also included as the possibility to invest in energy efficiency measures. The forecast results in an increase of the total useful energy from 2006 to 2050 by 18 o/o. The growth is expected to be highest in the regions South and East. The industry remains at a constant level in the base case and increased or reduced energy demand is analysed as different scenarios with the TIMES-Norway model. The most important driver is the population growth. Together with the assumptions made it results in increased useful energy demand in the household and service sectors of 25 o/o and 57 % respectively.(au)

  5. Forecast of useful energy for the TIMES-Norway model

    Energy Technology Data Exchange (ETDEWEB)

    Rosenberg, Eva

    2012-07-25

    A regional forecast of useful energy demand in seven Norwegian regions is calculated based on an earlier work with a national forecast. This forecast will be input to the energy system model TIMES-Norway and analyses will result in forecasts of energy use of different energy carriers with varying external conditions (not included in this report). The forecast presented here describes the methodology used and the resulting forecast of useful energy. lt is based on information of the long-term development of the economy by the Ministry of Finance, projections of population growths from Statistics Norway and several other studies. The definition of a forecast of useful energy demand is not absolute, but depends on the purpose. One has to be careful not to include parts that are a part of the energy system model, such as energy efficiency measures. In the forecast presented here the influence of new building regulations and the prohibition of production of incandescent light bulbs in EU etc. are included. Other energy efficiency measures such as energy management, heat pumps, tightening of leaks etc. are modelled as technologies to invest in and are included in the TIMES-Norway model. The elasticity between different energy carriers are handled by the TIMES-Norway model and some elasticity is also included as the possibility to invest in energy efficiency measures. The forecast results in an increase of the total useful energy from 2006 to 2050 by 18 o/o. The growth is expected to be highest in the regions South and East. The industry remains at a constant level in the base case and increased or reduced energy demand is analysed as different scenarios with the TIMES-Norway model. The most important driver is the population growth. Together with the assumptions made it results in increased useful energy demand in the household and service sectors of 25 o/o and 57 % respectively.(au)

  6. Technologies Assessing Limb Bradykinesia in Parkinson’s Disease

    Science.gov (United States)

    Hasan, Hasan; Athauda, Dilan S.; Foltynie, Thomas; Noyce, Alastair J.

    2017-01-01

    Background: The MDS-UPDRS (Movement Disorders Society – Unified Parkinson’s Disease Rating Scale) is the most widely used scale for rating impairment in PD. Subscores measuring bradykinesia have low reliability that can be subject to rater variability. Novel technological tools can be used to overcome such issues. Objective: To systematically explore and describe the available technologies for measuring limb bradykinesia in PD that were published between 2006 and 2016. Methods: A systematic literature search using PubMed (MEDLINE), IEEE Xplore, Web of Science, Scopus and Engineering Village (Compendex and Inspec) databases was performed to identify relevant technologies published until 18 October 2016. Results: 47 technologies assessing bradykinesia in PD were identified, 17 of which offered home and clinic-based assessment whilst 30 provided clinic-based assessment only. Of the eligible studies, 7 were validated in a PD patient population only, whilst 40 were tested in both PD and healthy control groups. 19 of the 47 technologies assessed bradykinesia only, whereas 28 assessed other parkinsonian features as well. 33 technologies have been described in additional PD-related studies, whereas 14 are not known to have been tested beyond the pilot phase. Conclusion: Technology based tools offer advantages including objective motor assessment and home monitoring of symptoms, and can be used to assess response to intervention in clinical trials or routine care. This review provides an up-to-date repository and synthesis of the current literature regarding technology used for assessing limb bradykinesia in PD. The review also discusses the current trends with regards to technology and discusses future directions in development. PMID:28222539

  7. Health technology assessment. Evaluation of biomedical innovative technologies.

    Science.gov (United States)

    Turchetti, Giuseppe; Spadoni, Enza; Geisler, Eliezer Elie

    2010-01-01

    This article describes health technology assessment (HTA) as an evaluation tool that applies systematic methods of inquiry to the generation and use of health technologies and new products. The focus of this article is on the contributions of HTA to the management of the new product development effort in the biomedical organization. Critical success factors (CSFs) are listed, and their role in assessing success is defined and explained. One of the conclusions of this article is that HTA is a powerful tool for managers in the biomedical sector, allowing them to better manage their innovation effort in their continuing struggle for competitiveness and survival.

  8. Recent Progress of Solar Weather Forecasting at Naoc

    Science.gov (United States)

    He, Han; Wang, Huaning; Du, Zhanle; Zhang, Liyun; Huang, Xin; Yan, Yan; Fan, Yuliang; Zhu, Xiaoshuai; Guo, Xiaobo; Dai, Xinghua

    The history of solar weather forecasting services at National Astronomical Observatories, Chinese Academy of Sciences (NAOC) can be traced back to 1960s. Nowadays, NAOC is the headquarters of the Regional Warning Center of China (RWC-China), which is one of the members of the International Space Environment Service (ISES). NAOC is responsible for exchanging data, information and space weather forecasts of RWC-China with other RWCs. The solar weather forecasting services at NAOC cover short-term prediction (within two or three days), medium-term prediction (within several weeks), and long-term prediction (in time scale of solar cycle) of solar activities. Most efforts of the short-term prediction research are concentrated on the solar eruptive phenomena, such as flares, coronal mass ejections (CMEs) and solar proton events, which are the key driving sources of strong space weather disturbances. Based on the high quality observation data of the latest space-based and ground-based solar telescopes and with the help of artificial intelligence techniques, new numerical models with quantitative analyses and physical consideration are being developed for the predictions of solar eruptive events. The 3-D computer simulation technology is being introduced for the operational solar weather service platform to visualize the monitoring of solar activities, the running of the prediction models, as well as the presenting of the forecasting results. A new generation operational solar weather monitoring and forecasting system is expected to be constructed in the near future at NAOC.

  9. Long-term fashion forecast based on the sociological model of cyclic changes

    Directory of Open Access Journals (Sweden)

    А V Lebsak-Kleimans

    2010-09-01

    Full Text Available The concepts of social changes coined by classical sociology may be incorporated as the basis for the elaboration of social prognostication models which, in turn, may suitable for fashion forecast applied technologies development. In the framework of the given paper fashion is described as the phenomenon of collective behaviour. The principles of long-term fashion trends forecast are shown to be in line with the concepts of cyclic development.

  10. A mathematical model to forecast uranium production

    International Nuclear Information System (INIS)

    Camisani-Calzolari, F.A.G.M.

    1987-01-01

    The uranium production forecasting program described in this paper projects production from reasonably assured, estimated additional and speculative resources in the cost categories of less than $130/kg U. Originally designed to handle South African production, it has been expanded and redimensioned using available published information to forecast production for countries of the Western World. The program forecasts production from up to 400 plants over a period of fifty years and has built-in production models derived from documented historical data of the more important uranium provinces. It is particularly suitable to assess production capabilities on a national and global scale where variations in outputs for the individual plants tend to even out. The program is aimed at putting the uranium potential of any one country into a realistic perspective, and it could thus be useful for planning purposes and marketing strategies

  11. Winter wheat quality monitoring and forecasting system based on remote sensing and environmental factors

    International Nuclear Information System (INIS)

    Haiyang, Yu; Yanmei, Liu; Guijun, Yang; Xiaodong, Yang; Chenwei, Nie; Dong, Ren

    2014-01-01

    To achieve dynamic winter wheat quality monitoring and forecasting in larger scale regions, the objective of this study was to design and develop a winter wheat quality monitoring and forecasting system by using a remote sensing index and environmental factors. The winter wheat quality trend was forecasted before the harvest and quality was monitored after the harvest, respectively. The traditional quality-vegetation index from remote sensing monitoring and forecasting models were improved. Combining with latitude information, the vegetation index was used to estimate agronomy parameters which were related with winter wheat quality in the early stages for forecasting the quality trend. A combination of rainfall in May, temperature in May, illumination at later May, the soil available nitrogen content and other environmental factors established the quality monitoring model. Compared with a simple quality-vegetation index, the remote sensing monitoring and forecasting model used in this system get greatly improved accuracy. Winter wheat quality was monitored and forecasted based on the above models, and this system was completed based on WebGIS technology. Finally, in 2010 the operation process of winter wheat quality monitoring system was presented in Beijing, the monitoring and forecasting results was outputted as thematic maps

  12. Independent Assessment of Technology Characterizations to Support the Biomass Program Annual State-of-Technology Assessments

    Energy Technology Data Exchange (ETDEWEB)

    Yeh, B.

    2011-03-01

    This report discusses an investigation that addressed two thermochemical conversion pathways for the production of liquid fuels and addressed the steps to the process, the technology providers, a method for determining the state of technology and a tool to continuously assess the state of technology. This report summarizes the findings of the investigation as well as recommendations for improvements for future studies.

  13. Dynamic neural network modeling of HF radar current maps for forecasting oil spill trajectories

    International Nuclear Information System (INIS)

    Tissot, P.; Perez, J.; Kelly, F.J.; Bonner, J.; Michaud, P.

    2001-01-01

    This paper examined the concept of dynamic neural network (NN) modeling for short-term forecasts of coastal high-frequency (HF) radar current maps offshore of Galveston Texas. HF radar technology is emerging as a viable and affordable way to measure surface currents in real time and the number of users applying the technology is increasing. A 25 megahertz, two site, Seasonde HF radar system was used to map ocean and bay surface currents along the coast of Texas where wind and river discharge create complex and rapidly changing current patters that override the weaker tidal flow component. The HF radar system is particularly useful in this type of setting because its mobility makes it a good marine spill response tool that could provide hourly current maps. This capability helps improve deployment of response resources. In addition, the NN model recently developed by the Conrad Blucher Institute can be used to forecast water levels during storm events. Forecasted currents are based on time series of current vectors from HF radar plus wind speed, wind direction, and water levels, as well as tidal forecasts. The dynamic NN model was tested to evaluate its performance and the results were compared with a baseline model which assumes the currents do not change from the time of the forecast up to the forecasted time. The NN model showed improvements over the baseline model for forecasting time equal or greater than 3 hours, but the difference was relatively small. The test demonstrated the ability of the dynamic NN model to link meteorological forcing functions with HF radar current maps. Development of the dynamic NN modeling is still ongoing. 18 refs., 1 tab., 5 figs

  14. Technology Assessment and Roadmap for the Emergency Radiation Dose Assessment Program

    International Nuclear Information System (INIS)

    Turteltaub, K W; Hartman-Siantar, C; Easterly, C; Blakely, W

    2005-01-01

    A Joint Interagency Working Group (JIWG) under the auspices of the Department of Homeland Security Office of Research and Development conducted a technology assessment of emergency radiological dose assessment capabilities as part of the overall need for rapid emergency medical response in the event of a radiological terrorist event in the United States. The goal of the evaluation is to identify gaps and recommend general research and development needs to better prepare the Country for mitigating the effects of such an event. Given the capabilities and roles for responding to a radiological event extend across many agencies, a consensus of gaps and suggested development plans was a major goal of this evaluation and road-mapping effort. The working group consisted of experts representing the Departments of Homeland Security, Health and Human Services (Centers for Disease Control and the National Institutes of Health), Food and Drug Administration, Department of Defense and the Department of Energy's National Laboratories (see appendix A for participants). The specific goals of this Technology Assessment and Roadmap were to: (1) Describe the general context for deployment of emergency radiation dose assessment tools following terrorist use of a radiological or nuclear device; (2) Assess current and emerging dose assessment technologies; and (3) Put forward a consensus high-level technology roadmap for interagency research and development in this area. This report provides a summary of the consensus of needs, gaps and recommendations for a research program in the area of radiation dosimetry for early response, followed by a summary of the technologies available and on the near-term horizon. We then present a roadmap for a research program to bring present and emerging near-term technologies to bear on the gaps in radiation dose assessment and triage. Finally we present detailed supporting discussion on the nature of the threats we considered, the status of technology

  15. Technology Assessment and Roadmap for the Emergency Radiation Dose Assessment Program

    Energy Technology Data Exchange (ETDEWEB)

    Turteltaub, K W; Hartman-Siantar, C; Easterly, C; Blakely, W

    2005-10-03

    A Joint Interagency Working Group (JIWG) under the auspices of the Department of Homeland Security Office of Research and Development conducted a technology assessment of emergency radiological dose assessment capabilities as part of the overall need for rapid emergency medical response in the event of a radiological terrorist event in the United States. The goal of the evaluation is to identify gaps and recommend general research and development needs to better prepare the Country for mitigating the effects of such an event. Given the capabilities and roles for responding to a radiological event extend across many agencies, a consensus of gaps and suggested development plans was a major goal of this evaluation and road-mapping effort. The working group consisted of experts representing the Departments of Homeland Security, Health and Human Services (Centers for Disease Control and the National Institutes of Health), Food and Drug Administration, Department of Defense and the Department of Energy's National Laboratories (see appendix A for participants). The specific goals of this Technology Assessment and Roadmap were to: (1) Describe the general context for deployment of emergency radiation dose assessment tools following terrorist use of a radiological or nuclear device; (2) Assess current and emerging dose assessment technologies; and (3) Put forward a consensus high-level technology roadmap for interagency research and development in this area. This report provides a summary of the consensus of needs, gaps and recommendations for a research program in the area of radiation dosimetry for early response, followed by a summary of the technologies available and on the near-term horizon. We then present a roadmap for a research program to bring present and emerging near-term technologies to bear on the gaps in radiation dose assessment and triage. Finally we present detailed supporting discussion on the nature of the threats we considered, the status of

  16. 20 Years of Technology and Language Assessment in "Language Learning & Technology"

    Science.gov (United States)

    Chapelle, Carol A.; Voss, Erik

    2016-01-01

    This review article provides an analysis of the research from the last two decades on the theme of technology and second language assessment. Based on an examination of the assessment scholarship published in "Language Learning & Technology" since its launch in 1997, we analyzed the review articles, research articles, book reviews,…

  17. Development of modelling algorithm of technological systems by statistical tests

    Science.gov (United States)

    Shemshura, E. A.; Otrokov, A. V.; Chernyh, V. G.

    2018-03-01

    The paper tackles the problem of economic assessment of design efficiency regarding various technological systems at the stage of their operation. The modelling algorithm of a technological system was performed using statistical tests and with account of the reliability index allows estimating the level of machinery technical excellence and defining the efficiency of design reliability against its performance. Economic feasibility of its application shall be determined on the basis of service quality of a technological system with further forecasting of volumes and the range of spare parts supply.

  18. Communicating Uncertainty in Volcanic Ash Forecasts: Decision-Making and Information Preferences

    Science.gov (United States)

    Mulder, Kelsey; Black, Alison; Charlton-Perez, Andrew; McCloy, Rachel; Lickiss, Matthew

    2016-04-01

    The Robust Assessment and Communication of Environmental Risk (RACER) consortium, an interdisciplinary research team focusing on communication of uncertainty with respect to natural hazards, hosted a Volcanic Ash Workshop to discuss issues related to volcanic ash forecasting, especially forecast uncertainty. Part of the workshop was a decision game in which participants including forecasters, academics, and members of the Aviation Industry were given hypothetical volcanic ash concentration forecasts and asked whether they would approve a given flight path. The uncertainty information was presented in different formats including hazard maps, line graphs, and percent probabilities. Results from the decision game will be presented with a focus on information preferences, understanding of the forecasts, and whether different formats of the same volcanic ash forecast resulted in different flight decisions. Implications of this research will help the design and presentation of volcanic ash plume decision tools and can also help advise design of other natural hazard information.

  19. Strategic Forecasting

    DEFF Research Database (Denmark)

    Duus, Henrik Johannsen

    2016-01-01

    Purpose: The purpose of this article is to present an overview of the area of strategic forecasting and its research directions and to put forward some ideas for improving management decisions. Design/methodology/approach: This article is conceptual but also informed by the author’s long contact...... and collaboration with various business firms. It starts by presenting an overview of the area and argues that the area is as much a way of thinking as a toolbox of theories and methodologies. It then spells out a number of research directions and ideas for management. Findings: Strategic forecasting is seen...... as a rebirth of long range planning, albeit with new methods and theories. Firms should make the building of strategic forecasting capability a priority. Research limitations/implications: The article subdivides strategic forecasting into three research avenues and suggests avenues for further research efforts...

  20. Spatial electric load forecasting

    CERN Document Server

    Willis, H Lee

    2002-01-01

    Containing 12 new chapters, this second edition contains offers increased-coverage of weather correction and normalization of forecasts, anticipation of redevelopment, determining the validity of announced developments, and minimizing risk from over- or under-planning. It provides specific examples and detailed explanations of key points to consider for both standard and unusual utility forecasting situations, information on new algorithms and concepts in forecasting, a review of forecasting pitfalls and mistakes, case studies depicting challenging forecast environments, and load models illustrating various types of demand.

  1. Assessing the Effectiveness of the Cone of Probability as a Visual Means of Communicating Scientific Forecasts

    Science.gov (United States)

    Orlove, B. S.; Broad, K.; Meyer, R.

    2010-12-01

    We review the evolution, communication, and differing interpretations of the National Hurricane Center (NHC)'s "cone of uncertainty" hurricane forecast graphic, drawing on several related disciplines—cognitive psychology, visual anthropology, and risk communication theory. We examine the 2004 hurricane season, two specific hurricanes (Katrina 2005 and Ike 2008) and the 2010 hurricane season, still in progress. During the 2004 hurricane season, five named storms struck Florida. Our analysis of that season draws upon interviews with key government officials and media figures, archival research of Florida newspapers, analysis of public comments on the NHC cone of uncertainty graphic and a multiagency study of 2004 hurricane behavior. At that time, the hurricane forecast graphic was subject to misinterpretation by many members of the public. We identify several characteristics of this graphic that contributed to public misinterpretation. Residents overemphasized the specific track of the eye, failed to grasp the width of hurricanes, and generally did not recognize the timing of the passage of the hurricane. Little training was provided to emergency response managers in the interpretation of forecasts. In the following year, Katrina became a national scandal, further demonstrating the limitations of the cone as a means of leading to appropriate responses to forecasts. In the second half of the first decade of the 21st century, three major changes occurred in hurricane forecast communication: the forecasts themselves improved in terms of accuracy and lead time, the NHC made minor changes in the graphics and expanded the explanatory material that accompanies the graphics, and some efforts were made to reach out to emergency response planners and municipal officials to enhance their understanding of the forecasts and graphics. There were some improvements in the responses to Ike, though a number of deaths were due to inadequate evacuations, and property damage probably

  2. Evaluating Downscaling Methods for Seasonal Climate Forecasts over East Africa

    Science.gov (United States)

    Roberts, J. Brent; Robertson, Franklin R.; Bosilovich, Michael; Lyon, Bradfield; Funk, Chris

    2013-01-01

    The U.S. National Multi-Model Ensemble seasonal forecasting system is providing hindcast and real-time data streams to be used in assessing and improving seasonal predictive capacity. The NASA / USAID SERVIR project, which leverages satellite and modeling-based resources for environmental decision making in developing nations, is focusing on the evaluation of NMME forecasts specifically for use in impact modeling within hub regions including East Africa, the Hindu Kush-Himalayan (HKH) region and Mesoamerica. One of the participating models in NMME is the NASA Goddard Earth Observing System (GEOS5). This work will present an intercomparison of downscaling methods using the GEOS5 seasonal forecasts of temperature and precipitation over East Africa. The current seasonal forecasting system provides monthly averaged forecast anomalies. These anomalies must be spatially downscaled and temporally disaggregated for use in application modeling (e.g. hydrology, agriculture). There are several available downscaling methodologies that can be implemented to accomplish this goal. Selected methods include both a non-homogenous hidden Markov model and an analogue based approach. A particular emphasis will be placed on quantifying the ability of different methods to capture the intermittency of precipitation within both the short and long rain seasons. Further, the ability to capture spatial covariances will be assessed. Both probabilistic and deterministic skill measures will be evaluated over the hindcast period

  3. Multigenerational organisations: a challenge for technology and social change

    NARCIS (Netherlands)

    Millar-Schijf, Carla C.J.M.; Lockett, Martin

    2014-01-01

    This paper analyses demographic and organisational trends associated with an ageing workforce and introduces the articles in the special issue of Technological Forecasting and Social Change on Ageing2Agility: Multi-stakeholder Technological Forecasting for the Multi-generational Challenges in the

  4. Short-term spatio-temporal wind power forecast in robust look-ahead power system dispatch

    KAUST Repository

    Xie, Le

    2014-01-01

    We propose a novel statistical wind power forecast framework, which leverages the spatio-temporal correlation in wind speed and direction data among geographically dispersed wind farms. Critical assessment of the performance of spatio-temporal wind power forecast is performed using realistic wind farm data from West Texas. It is shown that spatio-temporal wind forecast models are numerically efficient approaches to improving forecast quality. By reducing uncertainties in near-term wind power forecasts, the overall cost benefits on system dispatch can be quantified. We integrate the improved forecast with an advanced robust look-ahead dispatch framework. This integrated forecast and economic dispatch framework is tested in a modified IEEE RTS 24-bus system. Numerical simulation suggests that the overall generation cost can be reduced by up to 6% using a robust look-ahead dispatch coupled with spatio-temporal wind forecast as compared with persistent wind forecast models. © 2013 IEEE.

  5. Air Quality Forecasting through Different Statistical and Artificial Intelligence Techniques

    Science.gov (United States)

    Mishra, D.; Goyal, P.

    2014-12-01

    Urban air pollution forecasting has emerged as an acute problem in recent years because there are sever environmental degradation due to increase in harmful air pollutants in the ambient atmosphere. In this study, there are different types of statistical as well as artificial intelligence techniques are used for forecasting and analysis of air pollution over Delhi urban area. These techniques are principle component analysis (PCA), multiple linear regression (MLR) and artificial neural network (ANN) and the forecasting are observed in good agreement with the observed concentrations through Central Pollution Control Board (CPCB) at different locations in Delhi. But such methods suffers from disadvantages like they provide limited accuracy as they are unable to predict the extreme points i.e. the pollution maximum and minimum cut-offs cannot be determined using such approach. Also, such methods are inefficient approach for better output forecasting. But with the advancement in technology and research, an alternative to the above traditional methods has been proposed i.e. the coupling of statistical techniques with artificial Intelligence (AI) can be used for forecasting purposes. The coupling of PCA, ANN and fuzzy logic is used for forecasting of air pollutant over Delhi urban area. The statistical measures e.g., correlation coefficient (R), normalized mean square error (NMSE), fractional bias (FB) and index of agreement (IOA) of the proposed model are observed in better agreement with the all other models. Hence, the coupling of statistical and artificial intelligence can be use for the forecasting of air pollutant over urban area.

  6. Japanese supercomputer technology

    International Nuclear Information System (INIS)

    Buzbee, B.L.; Ewald, R.H.; Worlton, W.J.

    1982-01-01

    In February 1982, computer scientists from the Los Alamos National Laboratory and Lawrence Livermore National Laboratory visited several Japanese computer manufacturers. The purpose of these visits was to assess the state of the art of Japanese supercomputer technology and to advise Japanese computer vendors of the needs of the US Department of Energy (DOE) for more powerful supercomputers. The Japanese foresee a domestic need for large-scale computing capabilities for nuclear fusion, image analysis for the Earth Resources Satellite, meteorological forecast, electrical power system analysis (power flow, stability, optimization), structural and thermal analysis of satellites, and very large scale integrated circuit design and simulation. To meet this need, Japan has launched an ambitious program to advance supercomputer technology. This program is described

  7. Forecasting wind-driven wildfires using an inverse modelling approach

    Directory of Open Access Journals (Sweden)

    O. Rios

    2014-06-01

    Full Text Available A technology able to rapidly forecast wildfire dynamics would lead to a paradigm shift in the response to emergencies, providing the Fire Service with essential information about the ongoing fire. This paper presents and explores a novel methodology to forecast wildfire dynamics in wind-driven conditions, using real-time data assimilation and inverse modelling. The forecasting algorithm combines Rothermel's rate of spread theory with a perimeter expansion model based on Huygens principle and solves the optimisation problem with a tangent linear approach and forward automatic differentiation. Its potential is investigated using synthetic data and evaluated in different wildfire scenarios. The results show the capacity of the method to quickly predict the location of the fire front with a positive lead time (ahead of the event in the order of 10 min for a spatial scale of 100 m. The greatest strengths of our method are lightness, speed and flexibility. We specifically tailor the forecast to be efficient and computationally cheap so it can be used in mobile systems for field deployment and operativeness. Thus, we put emphasis on producing a positive lead time and the means to maximise it.

  8. Social Shaping in Danish Technology Assessment

    DEFF Research Database (Denmark)

    Hansen, Anne Grethe; Clausen, Christian

    2003-01-01

    The term ‘social shaping of technology’ has been used broadly as a response to techno-economic deterministic understandings of the relations between technology and society. Social shaping has brought together analysts from different backgrounds who share a common interest in the role of social an...... in these projects contributed to new insights into the processes of technological change and thus to policy formulation. The social shaping perspective and technology assessment experiences are suggested as important guides to future technology strategies....... and political action for technology change. The authors of this article suggest that the social shaping perspective draws on lessons from technology assessments of earlier decades, lessons about the role of technology debate, participation and democratic control. We suggest that these are important......The term ‘social shaping of technology’ has been used broadly as a response to techno-economic deterministic understandings of the relations between technology and society. Social shaping has brought together analysts from different backgrounds who share a common interest in the role of social...

  9. Electricity demand forecasting techniques

    International Nuclear Information System (INIS)

    Gnanalingam, K.

    1994-01-01

    Electricity demand forecasting plays an important role in power generation. The two areas of data that have to be forecasted in a power system are peak demand which determines the capacity (MW) of the plant required and annual energy demand (GWH). Methods used in electricity demand forecasting include time trend analysis and econometric methods. In forecasting, identification of manpower demand, identification of key planning factors, decision on planning horizon, differentiation between prediction and projection (i.e. development of different scenarios) and choosing from different forecasting techniques are important

  10. Multi-parametric variational data assimilation for hydrological forecasting

    Science.gov (United States)

    Alvarado-Montero, R.; Schwanenberg, D.; Krahe, P.; Helmke, P.; Klein, B.

    2017-12-01

    Ensemble forecasting is increasingly applied in flow forecasting systems to provide users with a better understanding of forecast uncertainty and consequently to take better-informed decisions. A common practice in probabilistic streamflow forecasting is to force deterministic hydrological model with an ensemble of numerical weather predictions. This approach aims at the representation of meteorological uncertainty but neglects uncertainty of the hydrological model as well as its initial conditions. Complementary approaches use probabilistic data assimilation techniques to receive a variety of initial states or represent model uncertainty by model pools instead of single deterministic models. This paper introduces a novel approach that extends a variational data assimilation based on Moving Horizon Estimation to enable the assimilation of observations into multi-parametric model pools. It results in a probabilistic estimate of initial model states that takes into account the parametric model uncertainty in the data assimilation. The assimilation technique is applied to the uppermost area of River Main in Germany. We use different parametric pools, each of them with five parameter sets, to assimilate streamflow data, as well as remotely sensed data from the H-SAF project. We assess the impact of the assimilation in the lead time performance of perfect forecasts (i.e. observed data as forcing variables) as well as deterministic and probabilistic forecasts from ECMWF. The multi-parametric assimilation shows an improvement of up to 23% for CRPS performance and approximately 20% in Brier Skill Scores with respect to the deterministic approach. It also improves the skill of the forecast in terms of rank histogram and produces a narrower ensemble spread.

  11. Development of a forecast model for global air traffic emissions

    Energy Technology Data Exchange (ETDEWEB)

    Schaefer, Martin

    2012-07-01

    The thesis describes the methodology and results of a simulation model that quantifies fuel consumption and emissions of civil air traffic. Besides covering historical emissions, the model aims at forecasting emissions in the medium-term future. For this purpose, simulation models of aircraft and engine types are used in combination with a database of global flight movements and assumptions about traffic growth, fleet rollover and operational aspects. Results from an application of the model include emissions of scheduled air traffic for the years 2000 to 2010 as well as forecasted emissions until the year 2030. In a baseline scenario of the forecast, input assumptions (e.g. traffic growth rates) are in line with predictions by the aircraft industry. Considering the effects of advanced technologies of the short-term and medium-term future, the forecast focusses on fuel consumption and emissions of nitric oxides. Calculations for historical air traffic additionally cover emissions of carbon monoxide, unburned hydrocarbons and soot. Results are validated against reference data including studies by the International Civil Aviation Organization (ICAO) and simulation results from international research projects. (orig.)

  12. A forecasting model of gaming revenues in Clark County, Nevada

    International Nuclear Information System (INIS)

    Edwards, B.; Bando, A.; Bassett, G.; Rosen, A.; Carlson, J.; Meenan, C.

    1992-01-01

    This paper describes the Western Area Gaining and Economic Response Simulator (WAGERS), a forecasting model that emphasizes the role of the gaming industry in Clark County, Nevada. It is designed to generate forecasts of gaming revenues in Clark County, whose regional economy is dominated by the gaming industry, an identify the exogenous variables that affect gaming revenues. This model will provide baseline forecasts of Clark County gaming revenues in order to assess changes in gaming related economic activity resulting from future events like the siting of a permanent high-level radioactive waste repository at Yucca Mountain

  13. A forecasting model of gaming revenues in Clark County, Nevada

    International Nuclear Information System (INIS)

    Edwards, B.; Bando, A.; Basset, G.; Rosen, A.; Meenan, C.; Carlson, J.

    1992-01-01

    This paper describes the Western Area Gaming and Economic Response Simulator (WAGERS), a forecasting model that emphasizes the role of the gaming industry in Clark County, Nevada. It is designed to generate forecasts of gaming revenues in Clark County, whose regional economy is dominated by the gaming industry, and identify the exogenous variables that affect gaming revenues. This model will provide baseline forecasts of Clark County gaming revenues in order to assess changes in gaming related economic activity resulting from future events like the siting of a permanent high-level radioactive waste repository at Yucca Mountain

  14. A forecasting model of gaming revenues in Clark County, Nevada

    Energy Technology Data Exchange (ETDEWEB)

    Edwards, B.; Bando, A.; Bassett, G.; Rosen, A. [Argonne National Lab., IL (United States); Carlson, J.; Meenan, C. [Science Applications International Corp., Las Vegas, NV (United States)

    1992-04-01

    This paper describes the Western Area Gaming and Economic Response Simulator (WAGERS), a forecasting model that emphasizes the role of the gaming industry in Clark County, Nevada. It is designed to generate forecasts of gaming revenues in Clark County, whose regional economy is dominated by the gaming industry, an identify the exogenous variables that affect gaming revenues. This model will provide baseline forecasts of Clark County gaming revenues in order to assess changes in gaming related economic activity resulting from future events like the siting of a permanent high-level radioactive waste repository at Yucca Mountain.

  15. Air Pollution Forecasts: An Overview.

    Science.gov (United States)

    Bai, Lu; Wang, Jianzhou; Ma, Xuejiao; Lu, Haiyan

    2018-04-17

    Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies.

  16. Air Pollution Forecasts: An Overview

    Directory of Open Access Journals (Sweden)

    Lu Bai

    2018-04-01

    Full Text Available Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies.

  17. Air Pollution Forecasts: An Overview

    Science.gov (United States)

    Bai, Lu; Wang, Jianzhou; Lu, Haiyan

    2018-01-01

    Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies. PMID:29673227

  18. INTEGRATION OF FRACTAL AND NEURAL NETWORK TECHNOLOGIES IN PEDAGOGICAL MONITORING AND ASSESSMENT OF KNOWLEDGE OF TRAINEES

    Directory of Open Access Journals (Sweden)

    Svetlana N Dvoryatkina

    2017-12-01

    Full Text Available The possibility of statement and solution of the problem of searching of theoretical justification and development of efficient didactic mechanisms of the organization of process of pedagogical monitoring and assessment of level of knowledge of trainees can be based on convergence of the leading psychological and pedagogical, mathematical, and informational technologies with accounting of the modern achievements in science. In the article, the pedagogical expediency of realization of opportunities of means of informational technologies in monitoring and assessment of the composite mathematical knowledge, in the management of cognitive activity of students is proved. The ability to integrate fractal methods and neural network technologies in perfecting of a system of pedagogical monitoring of mathematical knowledge of trainees as a part of the automated training systems (ATS is investigated and realized in practice. It is proved that fractal methods increase the accuracy and depth of estimation of the level of proficiency of students and also complexes of intellectual operations of the integrative qualities allowing to master and apply cross-disciplinary knowledge and abilities in professional activity. Neural network technologies solve a problem of realization of the personal focused tutoring from positions of optimum individualization of mathematical education and self-realization of the person. The technology of projection of integrative system of pedagogical monitoring of knowledge of students includes the following stages: establishment of the required tutoring parameters; definition and preparation of input data for realization of integration of fractal and neural network technologies; development of the diagnostic module as a part of the block of an artificial intelligence of ATS, filling of the databases structured by system; start of system for obtaining the forecast. In development of the integrative automated system of pedagogical

  19. Using forecast modelling to evaluate treatment effects in single-group interrupted time series analysis.

    Science.gov (United States)

    Linden, Ariel

    2018-05-11

    Interrupted time series analysis (ITSA) is an evaluation methodology in which a single treatment unit's outcome is studied serially over time and the intervention is expected to "interrupt" the level and/or trend of that outcome. ITSA is commonly evaluated using methods which may produce biased results if model assumptions are violated. In this paper, treatment effects are alternatively assessed by using forecasting methods to closely fit the preintervention observations and then forecast the post-intervention trend. A treatment effect may be inferred if the actual post-intervention observations diverge from the forecasts by some specified amount. The forecasting approach is demonstrated using the effect of California's Proposition 99 for reducing cigarette sales. Three forecast models are fit to the preintervention series-linear regression (REG), Holt-Winters (HW) non-seasonal smoothing, and autoregressive moving average (ARIMA)-and forecasts are generated into the post-intervention period. The actual observations are then compared with the forecasts to assess intervention effects. The preintervention data were fit best by HW, followed closely by ARIMA. REG fit the data poorly. The actual post-intervention observations were above the forecasts in HW and ARIMA, suggesting no intervention effect, but below the forecasts in the REG (suggesting a treatment effect), thereby raising doubts about any definitive conclusion of a treatment effect. In a single-group ITSA, treatment effects are likely to be biased if the model is misspecified. Therefore, evaluators should consider using forecast models to accurately fit the preintervention data and generate plausible counterfactual forecasts, thereby improving causal inference of treatment effects in single-group ITSA studies. © 2018 John Wiley & Sons, Ltd.

  20. Forecast Accuracy Uncertainty and Momentum

    OpenAIRE

    Bing Han; Dong Hong; Mitch Warachka

    2009-01-01

    We demonstrate that stock price momentum and earnings momentum can result from uncertainty surrounding the accuracy of cash flow forecasts. Our model has multiple information sources issuing cash flow forecasts for a stock. The investor combines these forecasts into an aggregate cash flow estimate that has minimal mean-squared forecast error. This aggregate estimate weights each cash flow forecast by the estimated accuracy of its issuer, which is obtained from their past forecast errors. Mome...

  1. Pavement condition assessment to forecast maintenance program on JKR state roads in Petaling district

    Science.gov (United States)

    Hamsan, R.; Hafiz, H.; Azlan, A.; Keprawi, M. F.; Malik, A. K. A.; Adamuddin, A.; Abdullah, A. H.; Shafie, A. M.

    2018-02-01

    This research allows local authorities to project road maintenance in term of activities and financial expenditure through pavement condition assessment and then Highway Development and Management (HDM-4) analysis. Current form of road maintenance carried out by local authority is on reactive manner where corrective actions were taken based on reports recorded. Some went unrecorded hence causing prolonged damages. This causes the local authority unable to project the required cost to maintain the roads. This affects the socio-economy of the surrounding routes. Hence, it is seen, as preventive maintenance of the roads will provide more feasible option in term of work force and finance to the local authority. To overcome this issue, a preventive model was introduced. This was done through pavement condition assessment (PCA) where analysis was done through HDM-4. Nondestructive test and destructive test were conducted in order to provide an indicator to the road's health. This were then analyzed in HDM-4 where the result was benchmarked with maintenance standard. The scope of this research is set to PCA where DT and NDT were performed on the routes of Petaling and the output is analyzed in HDM-4. The result of this research provides a 10 years forecast maintenance budget in maintaining the roads in Petaling. This allows the local authority to perform good practice in term of maintaining the roads while at the same time helps them in forecasting their budget for the upcoming years. This research will have a strong impact on the local socio-economy as well as local road user confidence towards the authority over good practices. This research can be further expanded to other type of roads as well as highway bridges.

  2. Forecasting in Complex Systems

    Science.gov (United States)

    Rundle, J. B.; Holliday, J. R.; Graves, W. R.; Turcotte, D. L.; Donnellan, A.

    2014-12-01

    Complex nonlinear systems are typically characterized by many degrees of freedom, as well as interactions between the elements. Interesting examples can be found in the areas of earthquakes and finance. In these two systems, fat tails play an important role in the statistical dynamics. For earthquake systems, the Gutenberg-Richter magnitude-frequency is applicable, whereas for daily returns for the securities in the financial markets are known to be characterized by leptokurtotic statistics in which the tails are power law. Very large fluctuations are present in both systems. In earthquake systems, one has the example of great earthquakes such as the M9.1, March 11, 2011 Tohoku event. In financial systems, one has the example of the market crash of October 19, 1987. Both were largely unexpected events that severely impacted the earth and financial systems systemically. Other examples include the M9.3 Andaman earthquake of December 26, 2004, and the Great Recession which began with the fall of Lehman Brothers investment bank on September 12, 2013. Forecasting the occurrence of these damaging events has great societal importance. In recent years, national funding agencies in a variety of countries have emphasized the importance of societal relevance in research, and in particular, the goal of improved forecasting technology. Previous work has shown that both earthquakes and financial crashes can be described by a common Landau-Ginzburg-type free energy model. These metastable systems are characterized by fat tail statistics near the classical spinodal. Correlations in these systems can grow and recede, but do not imply causation, a common source of misunderstanding. In both systems, a common set of techniques can be used to compute the probabilities of future earthquakes or crashes. In this talk, we describe the basic phenomenology of these systems and emphasize their similarities and differences. We also consider the problem of forecast validation and verification

  3. A Public-Private-Acadmic Partnership to Advance Solar Power Forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Haupt, Sue Ellen [National Center for Atmospheric Research, Boulder, CO (United States)

    2016-04-19

    The National Center for Atmospheric Research (NCAR) is pleased to have led a partnership to advance the state-of-the-science of solar power forecasting by designing, developing, building, deploying, testing, and assessing the SunCast™ Solar Power Forecasting System. The project has included cutting edge research, testing in several geographically- and climatologically-diverse high penetration solar utilities and Independent System Operators (ISOs), and wide dissemination of the research results to raise the bar on solar power forecasting technology. The partners include three other national laboratories, six universities, and industry partners. This public-private-academic team has worked in concert to perform use-inspired research to advance solar power forecasting through cutting-edge research to advance both the necessary forecasting technologies and the metrics for evaluating them. The project has culminated in a year-long, full-scale demonstration of provide irradiance and power forecasts to utilities and ISOs to use in their operations. The project focused on providing elements of a value chain, beginning with the weather that causes a deviation from clear sky irradiance and progresses through monitoring and observations, modeling, forecasting, dissemination and communication of the forecasts, interpretation of the forecast, and through decision-making, which produces outcomes that have an economic value. The system has been evaluated using metrics developed specifically for this project, which has provided rich information on model and system performance. Research was accomplished on the very short range (0-6 hours) Nowcasting system as well as on the longer term (6-72 hour) forecasting system. The shortest range forecasts are based on observations in the field. The shortest range system, built by Brookhaven National Laboratory (BNL) and based on Total Sky Imagers (TSIs) is TSICast, which operates on the shortest time scale with a latency of only a few

  4. Variable Selection in Time Series Forecasting Using Random Forests

    Directory of Open Access Journals (Sweden)

    Hristos Tyralis

    2017-10-01

    Full Text Available Time series forecasting using machine learning algorithms has gained popularity recently. Random forest is a machine learning algorithm implemented in time series forecasting; however, most of its forecasting properties have remained unexplored. Here we focus on assessing the performance of random forests in one-step forecasting using two large datasets of short time series with the aim to suggest an optimal set of predictor variables. Furthermore, we compare its performance to benchmarking methods. The first dataset is composed by 16,000 simulated time series from a variety of Autoregressive Fractionally Integrated Moving Average (ARFIMA models. The second dataset consists of 135 mean annual temperature time series. The highest predictive performance of RF is observed when using a low number of recent lagged predictor variables. This outcome could be useful in relevant future applications, with the prospect to achieve higher predictive accuracy.

  5. Ecological forecasting under climate change: the case of Baltic cod

    DEFF Research Database (Denmark)

    Lindegren, Martin; Möllmann, Christian; Nielsen, Anders

    2010-01-01

    Good decision making for fisheries and marine ecosystems requires a capacity to anticipate the consequences of management under different scenarios of climate change. The necessary ecological forecasting calls for ecosystem-based models capable of integrating multiple drivers across trophic levels...... and properly including uncertainty. The methodology presented here assesses the combined impacts of climate and fishing on marine food-web dynamics and provides estimates of the confidence envelope of the forecasts. It is applied to cod (Gadus morhua) in the Baltic Sea, which is vulnerable to climate......-related decline in salinity owing to both direct and indirect effects (i.e. through species interactions) on early-life survival. A stochastic food web-model driven by regional climate scenarios is used to produce quantitative forecasts of cod dynamics in the twenty-first century. The forecasts show how...

  6. Evaluation of ensemble precipitation forecasts generated through post-processing in a Canadian catchment

    Science.gov (United States)

    Jha, Sanjeev K.; Shrestha, Durga L.; Stadnyk, Tricia A.; Coulibaly, Paulin

    2018-03-01

    Flooding in Canada is often caused by heavy rainfall during the snowmelt period. Hydrologic forecast centers rely on precipitation forecasts obtained from numerical weather prediction (NWP) models to enforce hydrological models for streamflow forecasting. The uncertainties in raw quantitative precipitation forecasts (QPFs) are enhanced by physiography and orography effects over a diverse landscape, particularly in the western catchments of Canada. A Bayesian post-processing approach called rainfall post-processing (RPP), developed in Australia (Robertson et al., 2013; Shrestha et al., 2015), has been applied to assess its forecast performance in a Canadian catchment. Raw QPFs obtained from two sources, Global Ensemble Forecasting System (GEFS) Reforecast 2 project, from the National Centers for Environmental Prediction, and Global Deterministic Forecast System (GDPS), from Environment and Climate Change Canada, are used in this study. The study period from January 2013 to December 2015 covered a major flood event in Calgary, Alberta, Canada. Post-processed results show that the RPP is able to remove the bias and reduce the errors of both GEFS and GDPS forecasts. Ensembles generated from the RPP reliably quantify the forecast uncertainty.

  7. An Integrated Modeling Approach for Forecasting Long-Term Energy Demand in Pakistan

    OpenAIRE

    Syed Aziz Ur Rehman; Yanpeng Cai; Rizwan Fazal; Gordhan Das Walasai; Nayyar Hussain Mirjat

    2017-01-01

    Energy planning and policy development require an in-depth assessment of energy resources and long-term demand forecast estimates. Pakistan, unfortunately, lacks reliable data on its energy resources as well do not have dependable long-term energy demand forecasts. As a result, the policy makers could not come up with an effective energy policy in the history of the country. Energy demand forecast has attained greatest ever attention in the perspective of growing population and diminishing fo...

  8. Forecasting Japanese encephalitis incidence from historical morbidity patterns: Statistical analysis with 27 years of observation in Assam, India.

    Science.gov (United States)

    Handique, Bijoy K; Khan, Siraj A; Mahanta, J; Sudhakar, S

    2014-09-01

    Japanese encephalitis (JE) is one of the dreaded mosquito-borne viral diseases mostly prevalent in south Asian countries including India. Early warning of the disease in terms of disease intensity is crucial for taking adequate and appropriate intervention measures. The present study was carried out in Dibrugarh district in the state of Assam located in the northeastern region of India to assess the accuracy of selected forecasting methods based on historical morbidity patterns of JE incidence during the past 22 years (1985-2006). Four selected forecasting methods, viz. seasonal average (SA), seasonal adjustment with last three observations (SAT), modified method adjusting long-term and cyclic trend (MSAT), and autoregressive integrated moving average (ARIMA) have been employed to assess the accuracy of each of the forecasting methods. The forecasting methods were validated for five consecutive years from 2007-2012 and accuracy of each method has been assessed. The forecasting method utilising seasonal adjustment with long-term and cyclic trend emerged as best forecasting method among the four selected forecasting methods and outperformed the even statistically more advanced ARIMA method. Peak of the disease incidence could effectively be predicted with all the methods, but there are significant variations in magnitude of forecast errors among the selected methods. As expected, variation in forecasts at primary health centre (PHC) level is wide as compared to that of district level forecasts. The study showed that adopted forecasting techniques could reasonably forecast the intensity of JE cases at PHC level without considering the external variables. The results indicate that the understanding of long-term and cyclic trend of the disease intensity will improve the accuracy of the forecasts, but there is a need for making the forecast models more robust to explain sudden variation in the disease intensity with detail analysis of parasite and host population

  9. klax Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  10. kprc Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  11. katl Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  12. kmcn Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  13. kogb Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  14. kama Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  15. ptkk Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  16. kiwa Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  17. kavp Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  18. kdca Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  19. kbwg Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  20. kdfw Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  1. kssi Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  2. pahn Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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  13. kdro Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  14. kmce Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  15. ktpa Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  16. kmot Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  17. kcre Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  18. klws Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  19. kotm Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  20. khqm Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...